See my Google Scholar profile for bibliometrics, or arXiv for preprints. If you’re having trouble accessing any paper at a publisher’s site, just contact me for a PDF by email. My responses to government consultations are here.

2026

@inproceedings{bulychev2026where,
  author = {Maria Bulychev and Neil G. Marchant and Benjamin I. P. Rubinstein},
  title = {Where is the Watermark? Interpretable Watermark Detection at the Block Level},
  year = {2026},
  booktitle = {Proceedings of the Winter Conference on Applications of Computer Vision},
  series = {WACV},
  note = {Accepted},
}

• Bulychev, Maria, Neil G. Marchant, and Benjamin I. P. Rubinstein. “Where is the Watermark? Interpretable Watermark Detection at the Block Level”. In: Proceedings of the Winter Conference on Applications of Computer Vision. WACV. Accepted. 2026 [BibTeX]

2025

@inproceedings{marchant2025adaptive,
  title = {Adaptive Data Analysis for Growing Data},
  author = {Neil G. Marchant and Benjamin I. P. Rubinstein},
  year = {2025},
  booktitle = {Advances in Neural Information Processing Systems},
  series = {NeurIPS},
  note = {Accepted},
}

• Marchant, Neil G. and Benjamin I. P. Rubinstein. “Adaptive Data Analysis for Growing Data”. In: Advances in Neural Information Processing Systems. NeurIPS. Accepted. 2025 [PDF; BibTeX]

@inproceedings{huang2025adaptdel,
  author = {Zhuoqun Huang and Neil G. Marchant and Olga Ohrimenko and Benjamin I. P. Rubinstein},
  title = {{AdaptDel}: Adaptable Deletion Rate Randomized Smoothing for Certified Robustness},
  year = {2025},
  booktitle = {Advances in Neural Information Processing Systems},
  series = {NeurIPS},
  note = {Accepted},
}

• Huang, Zhuoqun, Neil G. Marchant, Olga Ohrimenko, and Benjamin I. P. Rubinstein. “AdaptDel: Adaptable Deletion Rate Randomized Smoothing for Certified Robustness”. In: Advances in Neural Information Processing Systems. NeurIPS. Accepted. 2025 [PDF; BibTeX]

@inproceedings{cullen2025position,
  title = {Position: Certified Robustness Does Not (Yet) Imply Model Security},
  author = {Andrew C. Cullen and Paul Montague and Sarah M. Erfani and Benjamin I. P. Rubinstein},
  year = {2025},
  booktitle = {Proceedings of the 42nd International Conference on Machine Learning},
  series = {ICML},
  pages = {81185--81198},
}

• Cullen, Andrew C., Paul Montague, Sarah M. Erfani, and Benjamin I. P. Rubinstein. “Position: Certified Robustness Does Not (Yet) Imply Model Security”. In: Proceedings of the 42nd International Conference on Machine Learning. ICML. 2025, pp. 81185-81198 [Selected as Oral; publisher link; PDF; BibTeX]

@inproceedings{zhang2025one,
  title = {One Stone, Two Birds: Enhancing Adversarial Defense Through the Lens of Distributional Discrepancy},
  author = {Jiacheng Zhang and Benjamin I. P. Rubinstein and Jingfeng Zhang and Feng Liu},
  year = {2025},
  booktitle = {Proceedings of the 42nd International Conference on Machine Learning},
  series = {ICML},
  pages = {75951--75970},
}

• Zhang, Jiacheng, Benjamin I. P. Rubinstein, Jingfeng Zhang, and Feng Liu. “One Stone, Two Birds: Enhancing Adversarial Defense Through the Lens of Distributional Discrepancy”. In: Proceedings of the 42nd International Conference on Machine Learning. ICML. 2025, pp. 75951-75970 [publisher link; PDF; code; BibTeX]

@inproceedings{liu2025multilevel,
  author = {Shijie Liu and Andrew C. Cullen and Paul Montague and Sarah M. Erfani and Benjamin I. P. Rubinstein},
  title = {Multi-level Certified Defense Against Poisoning Attacks in Offline Reinforcement Learning},
  year = {2025},
  booktitle = {International Conference on Representation Learning},
  series = {ICLR},
  pages = {44885--44905},
}

• Liu, Shijie, Andrew C. Cullen, Paul Montague, Sarah M. Erfani, and Benjamin I. P. Rubinstein. “Multi-level Certified Defense Against Poisoning Attacks in Offline Reinforcement Learning”. In: International Conference on Representation Learning. ICLR. 2025, pp. 44885-44905 [publisher link; PDF; BibTeX]

@article{rekavandi24rsreg,
  title = {{RS-Reg}: {P}robabilistic and Robust Certified Regression Through Randomized Smoothing},
  author = {Aref Miri Rekavandi and Olga Ohrimenko and Benjamin I. P. Rubinstein},
  journal = {Transactions on Machine Learning Research},
  year = {2025},
}

• Rekavandi, Aref Miri, Olga Ohrimenko, and Benjamin I. P. Rubinstein. “RS-Reg: Probabilistic and Robust Certified Regression Through Randomized Smoothing”. In: Transactions on Machine Learning Research (2025). [publisher link; PDF; code; BibTeX]

@inproceedings{he2025tuba,
  title = {{TUBA}: Cross-Lingual Transferability of Backdoor Attacks in {LLMs} with Instruction Tuning},
  author = {Xuanli He and Jun Wang and Qiongkai Xu and Pasquale Minervini and Pontus Stenetorp and Benjamin I. P. Rubinstein and Trevor Cohn},
  year = {2025},
  pages = {16504–16544},
  booktitle = {Findings of the Association for Computational Linguistics: ACL 2025},
  series = {ACL},
}

• He, Xuanli, Jun Wang, Qiongkai Xu, Pasquale Minervini, Pontus Stenetorp, Benjamin I. P. Rubinstein, and Trevor Cohn. “TUBA: Cross-Lingual Transferability of Backdoor Attacks in LLMs with Instruction Tuning”. In: Findings of the Association for Computational Linguistics: ACL 2025. ACL. 2025, p. 16504–16544 [publisher link; BibTeX]

@incollection{marchant2025data,
  title = {Data Privacy in Enterprise {AI}},
  author = {Neil G. Marchant and Ying Zhao and Benjamin I. P. Rubinstein and Olga Ohrimenko},
  booktitle = {Enterprise {AI}},
  editor = {Shazia Sadiq},
  pages = {129--181},
  year = {2025},
  publisher = {Springer},
}

• Marchant, Neil G., Ying Zhao, Benjamin I. P. Rubinstein, and Olga Ohrimenko. “Data Privacy in Enterprise AI”. In: Enterprise AI. Ed. by Shazia Sadiq. Springer, 2025, pp. 129-181 [publisher link; BibTeX]

@misc{yan2025dynamiq,
  title = {{DynamiQ}: Unlocking the Potential of Dynamic Task Allocation in Parallel Fuzzing},
  author = {Wenqi Yan and Toby Murray and Benjamin I.P. Rubinstein and Van-Thuan Pham},
  note = {arXiv:2510.04469 [cs.SE]},
  year = {2025},
  month = {Oct},
}

• Yan, Wenqi, Toby Murray, Benjamin I.P. Rubinstein, and Van-Thuan Pham. DynamiQ: Unlocking the Potential of Dynamic Task Allocation in Parallel Fuzzing. arXiv:2510.04469 [cs.SE]. Oct. 2025 [PDF; BibTeX]

2024

@inproceedings{rekavandi2024certified,
  author = {Aref Miri Rekavandi and Farhad Farokhi and Olga Ohrimenko and Benjamin I. P. Rubinstein},
  title = {Certified Adversarial Robustness via Randomized alpha-Smoothing for Regression Models},
  year = {2024},
  booktitle = {Advances in Neural Information Processing Systems},
  series = {NeurIPS},
  pages = {134127--134150},
}

• Rekavandi, Aref Miri, Farhad Farokhi, Olga Ohrimenko, and Benjamin I. P. Rubinstein. “Certified Adversarial Robustness via Randomized alpha-Smoothing for Regression Models”. In: Advances in Neural Information Processing Systems. NeurIPS. 2024, pp. 134127-134150 [publisher link; BibTeX]

@inproceedings{cullen2024et,
  title = {Et Tu Certifications: Robustness Certificates Yield Better Adversarial Examples},
  author = {Andrew C. Cullen and Paul Montague and Shijie Liu and Sarah M. Erfani and Benjamin I. P. Rubinstein},
  year = {2024},
  booktitle = {Proceedings of the 41st International Conference on Machine Learning},
  series = {ICML},
  pages = {9745--9761},
}

• Cullen, Andrew C., Paul Montague, Shijie Liu, Sarah M. Erfani, and Benjamin I. P. Rubinstein. “Et Tu Certifications: Robustness Certificates Yield Better Adversarial Examples”. In: Proceedings of the 41st International Conference on Machine Learning. ICML. 2024, pp. 9745-9761 [PDF; video; publisher link; BibTeX]

@inproceedings{jin2024elephants,
  title = {Elephants Do Not Forget: Differential Privacy with State Continuity for Privacy Budget },
  author = {Jiankai Jin and Chitchanok Chuengsatiansup and Toby Murray and Benjamin I. P. Rubinstein and Yuval Yarom and Olga Ohrimenko},
  year = {2024},
  booktitle = {Proceedings of the 2024 ACM SIGSAC Conference on Computer and Communications Security},
  series = {CCS},
  pages = {1909--1923},
}

• Jin, Jiankai, Chitchanok Chuengsatiansup, Toby Murray, Benjamin I. P. Rubinstein, Yuval Yarom, and Olga Ohrimenko. “Elephants Do Not Forget: Differential Privacy with State Continuity for Privacy Budget”. In: Proceedings of the 2024 ACM SIGSAC Conference on Computer and Communications Security. CCS. 2024, pp. 1909-1923 [PDF; publisher link; BibTeX]

@inproceedings{cullen2023its,
  title = {It's Simplex! Disaggregating Measures to Improve Certified Robustness},
  author = {Andrew C. Cullen and Paul Montague and Shijie Liu and Sarah Erfani and Benjamin I. P. Rubinstein},
  year = {2024},
  booktitle = {2024 IEEE Symposium on Security and Privacy},
  series = {SP},
  pages = {2886--2900},
}

• Cullen, Andrew C., Paul Montague, Shijie Liu, Sarah Erfani, and Benjamin I. P. Rubinstein. “It’s Simplex! Disaggregating Measures to Improve Certified Robustness”. In: 2024 IEEE Symposium on Security and Privacy. SP. 2024, pp. 2886-2900 [PDF; publisher link; BibTeX]

@inproceedings{wang2024backdoor,
  title = {Backdoor Attacks on Multilingual Machine Translation},
  author = {Jun Wang and Qiongkai Xu and Xuanli He and Benjamin I. P. Rubinstein and Trevor Cohn},
  booktitle = {Proceedings of the 2024 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies},
  series = {NAACL},
  pages = {4515--4534},
  year = {2024},
}

• Wang, Jun, Qiongkai Xu, Xuanli He, Benjamin I. P. Rubinstein, and Trevor Cohn. “Backdoor Attacks on Multilingual Machine Translation”. In: Proceedings of the 2024 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies. NAACL. 2024, pp. 4515-4534 [Selected as Oral (15% of accepted papers); PDF; publisher link; BibTeX]

@article{he2024seep,
  title = {{SEEP}: Training Dynamics Grounds Latent Representation Search for Mitigating Backdoor Poisoning Attacks},
  author = {Xuanli He and Qiongkai Xu and Jun Wang and Benjamin I. P. Rubinstein and Trevor Cohn},
  journal = {Transactions of the Association for Computational Linguistics (TACL)},
  year = {2024},
  pages = {996--1010},
  volume = {12},
}

• He, Xuanli, Qiongkai Xu, Jun Wang, Benjamin I. P. Rubinstein, and Trevor Cohn. “SEEP: Training Dynamics Grounds Latent Representation Search for Mitigating Backdoor Poisoning Attacks”. In: Transactions of the Association for Computational Linguistics (TACL) 12 (2024), pp. 996-1010 [PDF; BibTeX]

@inproceedings{huang24certed,
  title = {{CERT-ED}: Certifiably Robust Text Classification for Edit Distance},
  author = {Zhuoqun Huang and Neil G. Marchant and Olga Ohrimenko and Benjamin I. P. Rubinstein},
  booktitle = {Findings of the Association for Computational Linguistics: EMNLP 2024},
  year = {2024},
  pages = {10813--10835},
}

• Huang, Zhuoqun, Neil G. Marchant, Olga Ohrimenko, and Benjamin I. P. Rubinstein. “CERT-ED: Certifiably Robust Text Classification for Edit Distance”. In: Findings of the Association for Computational Linguistics: EMNLP 2024. 2024, pp. 10813-10835 [PDF; code; publisher link; BibTeX]

@inproceedings{jin2024getting,
  title = {Getting a-Round Guarantees: Floating-Point Attacks on Certified
  Robustness},
  author = {Jiankai Jin and Olga Ohrimenko and Benjamin I. P. Rubinstein},
  year = {2024},
  booktitle = {Proceedings of the 17th ACM Workshop on Security and Artificial Intelligence},
  series = {AISec},
  pages = {53--64},
  note = {co-located with CCS2024},
}

• Jin, Jiankai, Olga Ohrimenko, and Benjamin I. P. Rubinstein. “Getting a-Round Guarantees: Floating-Point Attacks on Certified Robustness”. In: Proceedings of the 17th ACM Workshop on Security and Artificial Intelligence. AISec. co-located with CCS2024. 2024, pp. 53-64 [PDF; publisher link; BibTeX]

@inproceedings{joukhadar2024designing,
  author = {Zaher Joukhadar and Jonathan Morgan and Christopher Bayliss and Miguel {Ortiz del Castillo} and Jack McRobbie and Robert Mearns and Krista A. Ehinger and Benjamin I. P. Rubinstein and Richard Sinnott and Michele Trenti and James Bailey},
  title = {Designing an Adaptive {AI} System for Operation on Board the {SpIRIT} Nano-Satellite},
  year = {2024},
  pages = {329--341},
  booktitle = {37th Australasian Joint Conference on Artificial Intelligence},
  series = {AJCAI},
}

• Joukhadar, Zaher, Jonathan Morgan, Christopher Bayliss, Miguel Ortiz del Castillo, Jack McRobbie, Robert Mearns, Krista A. Ehinger, Benjamin I. P. Rubinstein, Richard Sinnott, Michele Trenti, and James Bailey. “Designing an Adaptive AI System for Operation on Board the SpIRIT Nano-Satellite”. In: 37th Australasian Joint Conference on Artificial Intelligence. AJCAI. 2024, pp. 329-341 [publisher link; BibTeX]

@inproceedings{oetomo24warm,
  title = {Warm-Starting Contextual Bandits under Latent Reward Scaling},
  year = {2024},
  author = {Bastian Oetomo and R. Malinga Perera and Renata Borovica-Gajic and Benjamin I. P. Rubinstein},
  booktitle = {2024 IEEE 16th International Conference on Data Mining},
  series = {ICDM},
  pages = {360--369},
}

• Oetomo, Bastian, R. Malinga Perera, Renata Borovica-Gajic, and Benjamin I. P. Rubinstein. “Warm-Starting Contextual Bandits under Latent Reward Scaling”. In: 2024 IEEE 16th International Conference on Data Mining. ICDM. 2024, pp. 360-369 [publisher link; BibTeX]

@misc{he2024transferring,
  title = {Transferring Troubles: Cross-Lingual Transferability of Backdoor Attacks in LLMs with Instruction Tuning},
  author = {Xuanli He and Jun Wang and Qiongkai Xu and Pasquale Minervini and Pontus Stenetorp and Benjamin I. P. Rubinstein and Trevor Cohn},
  note = {arXiv:2404.19597 [cs.CL]},
  year = {2024},
  month = {May},
}

• He, Xuanli, Jun Wang, Qiongkai Xu, Pasquale Minervini, Pontus Stenetorp, Benjamin I. P. Rubinstein, and Trevor Cohn. Transferring Troubles: Cross-Lingual Transferability of Backdoor Attacks in LLMs with Instruction Tuning. arXiv:2404.19597 [cs.CL]. May. 2024 [PDF; BibTeX]

2023

@inproceedings{huang2023rsdel,
  title = {{RS-Del}: Edit Distance Robustness Certificates for Sequence Classifiers via Randomized Deletion},
  author = {Zhuoqun Huang and Neil G Marchant and Keane Lucas and Lujo Bauer and Olga Ohrimenko and Benjamin I. P. Rubinstein},
  booktitle = {Advances in Neural Information Processing Systems},
  series = {NeurIPS},
  year = {2023},
  pages = {18676--18711},
}

• Huang, Zhuoqun, Neil G Marchant, Keane Lucas, Lujo Bauer, Olga Ohrimenko, and Benjamin I. P. Rubinstein. “RS-Del: Edit Distance Robustness Certificates for Sequence Classifiers via Randomized Deletion”. In: Advances in Neural Information Processing Systems. NeurIPS. 2023, pp. 18676-18711 [PDF; publisher link; code; BibTeX]

@inproceedings{he2023mitigating,
  title = {Mitigating Backdoor Poisoning Attacks through the Lens of Spurious Correlation},
  author = {Xuanli He and Qiongkai Xu and Jun Wang and Benjamin I. P. Rubinstein and Trevor Cohn},
  booktitle = {Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing},
  series = {EMNLP},
  pages = {953--967},
  year = {2023},
}

• He, Xuanli, Qiongkai Xu, Jun Wang, Benjamin I. P. Rubinstein, and Trevor Cohn. “Mitigating Backdoor Poisoning Attacks through the Lens of Spurious Correlation”. In: Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing. EMNLP. 2023, pp. 953-967 [publisher link; full; video; BibTeX]

@inproceedings{liu2023enhancing,
  title = {Enhancing the Antidote: Improved Pointwise Certifications against Poisoning Attacks},
  author = {Shijie Liu and Andrew C. Cullen and Paul Montague and Sarah Monazam Erfani and Benjamin I. P. Rubinstein},
  year = {2023},
  booktitle = {Proceedings of the 37th AAAI Conference on Artificial Intelligence},
  series = {AAAI},
  pages = {8861--8869},
}

• Liu, Shijie, Andrew C. Cullen, Paul Montague, Sarah Monazam Erfani, and Benjamin I. P. Rubinstein. “Enhancing the Antidote: Improved Pointwise Certifications against Poisoning Attacks”. In: Proceedings of the 37th AAAI Conference on Artificial Intelligence. AAAI. 2023, pp. 8861-8869 [publisher link; full; BibTeX]

@article{perera2023nodba,
  title = {No {DBA}? No regret! Multi-armed bandits for index tuning of analytical and {HTAP} workloads with provable guarantees},
  author = {R. Malinga Perera and Bastian Oetomo and Benjamin I. P. Rubinstein and Renata Borovica-Gajic},
  journal = {IEEE Transactions on Knowledge and Data Engineering},
  year = {2023},
  pages = {12855--12872},
  volume = {35},
  number = {12},
}

• Perera, R. Malinga, Bastian Oetomo, Benjamin I. P. Rubinstein, and Renata Borovica-Gajic. “No DBA? No regret! Multi-armed bandits for index tuning of analytical and HTAP workloads with provable guarantees”. In: IEEE Transactions on Knowledge and Data Engineering 35.12 (2023), pp. 12855-12872 [publisher link; full; BibTeX]

@article{marchant2023bayesian,
  title = {{B}ayesian Graphical Entity Resolution using Exchangeable Random Partition Priors},
  author = {Neil G. Marchant and Benjamin I. P. Rubinstein and Rebecca C. Steorts},
  year = {2023},
  journal = {Journal of Survey Statistics and Methodology},
  volume = {11},
  number = {3},
  pages = {569--596},
  month = {June},
  publisher = {Oxford University Press},
}

• Marchant, Neil G., Benjamin I. P. Rubinstein, and Rebecca C. Steorts. “Bayesian Graphical Entity Resolution using Exchangeable Random Partition Priors”. In: Journal of Survey Statistics and Methodology 11.3 (Jun. 2023), pp. 569-596 [publisher link; full; code; BibTeX]

@article{oetomo2023cutting,
  title = {Cutting to the Chase with Warm-Start Contextual Bandits},
  author = {Bastian Saputra Oetomo and R. Malinga Perera and Renata Borovica-Gajic and Benjamin I. P. Rubinstein},
  year = {2023},
  journal = {Knowledge and Information Systems},
  volume = {65},
  pages = {3533--3565},
}

• Oetomo, Bastian Saputra, R. Malinga Perera, Renata Borovica-Gajic, and Benjamin I. P. Rubinstein. “Cutting to the Chase with Warm-Start Contextual Bandits”. In: Knowledge and Information Systems 65 (2023), pp. 3533-3565 [publisher link; BibTeX]

@article{sun2023to,
  author = {Guoxin Sun and Tansu Alpcan and Benjamin I. P. Rubinstein and Seyit Camtepe},
  journal = {IEEE Transactions on Information Forensics and Security},
  title = {To Act or Not To Act: An Adversarial Game for Securing Vehicle Platoons},
  year = {2023},
  pages = {164--177},
  volume = {19},
}

• Sun, Guoxin, Tansu Alpcan, Benjamin I. P. Rubinstein, and Seyit Camtepe. “To Act or Not To Act: An Adversarial Game for Securing Vehicle Platoons”. In: IEEE Transactions on Information Forensics and Security 19 (2023), pp. 164-177 [publisher link; BibTeX]

@article{cullen2023predicting,
  title = {Predicting dynamic spectrum allocation: a review covering simulation, modelling, and prediction},
  author = {Andrew C. Cullen and Benjamin I. P. Rubinstein and Sithamparanathan Kandeepan and Barry Flower and Philip H. W. Leong},
  journal = {Artificial Intelligence Review},
  year = {2023},
  volume = {56},
  pages = {10921--10959},
}

• Cullen, Andrew C., Benjamin I. P. Rubinstein, Sithamparanathan Kandeepan, Barry Flower, and Philip H. W. Leong. “Predicting dynamic spectrum allocation: a review covering simulation, modelling, and prediction”. In: Artificial Intelligence Review 56 (2023), pp. 10921-10959 [publisher link; BibTeX]

@inproceedings{he2023imbert,
  title = {{IMBERT}: Making {BERT} Immune to Insertion-based Backdoor Attacks},
  author = {Xuanli He and Jun Wang and Benjamin Rubinstein and Trevor Cohn},
  booktitle = {Proceedings of the 3rd Workshop on Trustworthy Natural Language Processing},
  series = {TrustNLP},
  pages = {287--301},
  year = {2023},
}

• He, Xuanli, Jun Wang, Benjamin Rubinstein, and Trevor Cohn. “IMBERT: Making BERT Immune to Insertion-based Backdoor Attacks”. In: Proceedings of the 3rd Workshop on Trustworthy Natural Language Processing. TrustNLP. Co-located with ACL. 2023, pp. 287-301 [publisher link; BibTeX]

@inproceedings{sun2023an,
  title = {An Adversarial Strategic Game for Machine Learning as a Service using System Features},
  author = {Guoxin Sun and Tansu Alpcan and Andrew C. Cullen and Seyit Camtepe and Benjamin I. P. Rubinstein},
  booktitle = {Proceedings of the 2023 International Conference on Autonomous Agents and Multiagent Systems},
  series = {AAMAS},
  year = {2023},
  note = {Extended abstract},
  pages = {2508--2510},
}

• Sun, Guoxin, Tansu Alpcan, Andrew C. Cullen, Seyit Camtepe, and Benjamin I. P. Rubinstein. “An Adversarial Strategic Game for Machine Learning as a Service using System Features”. In: Proceedings of the 2023 International Conference on Autonomous Agents and Multiagent Systems. AAMAS. Extended abstract. 2023, pp. 2508-2510 [publisher link; BibTeX]

@inproceedings{liu2023efficient,
  title = {Efficient Index Learning via Model Reuse and Fine-tuning},
  author = {Guanli Liu and Jianzhong Qi and Lars Kulik and Kazuya Soga and Renata Borovica-Gajic and Benjamin I. P. Rubinstein},
  booktitle = {International Workshop on Databases and Machine Learning},
  series = {DBML},
  year = {2023},
}

• Liu, Guanli, Jianzhong Qi, Lars Kulik, Kazuya Soga, Renata Borovica-Gajic, and Benjamin I. P. Rubinstein. “Efficient Index Learning via Model Reuse and Fine-tuning”. In: International Workshop on Databases and Machine Learning. DBML. Co-located with ICDE. Accepted. 2023 [BibTeX]

@inproceedings{gao2023beyond,
  author = {Wentao Gao and Van-Thuan Pham and Dongge Liu and Oliver Chang and Toby Murray and Benjamin I.P. Rubinstein},
  title = {Beyond the Coverage Plateau: A Comprehensive Study of Fuzz Blockers (Registered Report)},
  year = {2023},
  booktitle = {Proceedings of the 2nd International Fuzzing Workshop},
  pages = {47--55},
  series = {FUZZING},
}

• Gao, Wentao, Van-Thuan Pham, Dongge Liu, Oliver Chang, Toby Murray, and Benjamin I.P. Rubinstein. “Beyond the Coverage Plateau: A Comprehensive Study of Fuzz Blockers (Registered Report)”. In: Proceedings of the 2nd International Fuzzing Workshop. FUZZING. 2023, pp. 47-55 [publisher link; BibTeX]

@inproceedings{zhang2023make,
  title = {Make Predictions Predictable: Fast Concept-based Counterfactual Explanations for Images},
  author = {Ruihan Zhang and Tim Miller and Krista Ehinger and Benjamin Rubinstein},
  booktitle = {Proceedings of the IJCAI 2023 Workshop on XAI},
  year = {2023},
}

• Zhang, Ruihan, Tim Miller, Krista Ehinger, and Benjamin Rubinstein. “Make Predictions Predictable: Fast Concept-based Counterfactual Explanations for Images”. In: Proceedings of the IJCAI 2023 Workshop on XAI. Co-located with IJCAI. 2023 [publisher link; BibTeX]

@inproceedings{zhang2023comparison,
  title = {Comparison of Supervised and Unsupervised Concepts in Concept-based Interpretable Models},
  author = {Ruihan Zhang and Tim Miller and Krista Ehinger and Benjamin Rubinstein},
  booktitle = {Proceedings of the IJCAI 2023 Workshop on XAI},
  year = {2023},
}

• Zhang, Ruihan, Tim Miller, Krista Ehinger, and Benjamin Rubinstein. “Comparison of Supervised and Unsupervised Concepts in Concept-based Interpretable Models”. In: Proceedings of the IJCAI 2023 Workshop on XAI. Co-located with IJCAI. 2023 [publisher link; BibTeX]

2022

@inproceedings{cullen2022double,
  title = {Double Bubble, Toil and Trouble: Enhancing Certified Robustness through Transitivity},
  author = {Andrew C. Cullen and Paul Montague and Shijie Liu and Sarah Monazam Erfani and Benjamin I. P. Rubinstein},
  booktitle = {Advances in Neural Information Processing Systems},
  series = {NeurIPS},
  year = {2022},
  pages = {19099--19112},
  volume = {35},
}

• Cullen, Andrew C., Paul Montague, Shijie Liu, Sarah Monazam Erfani, and Benjamin I. P. Rubinstein. “Double Bubble, Toil and Trouble: Enhancing Certified Robustness through Transitivity”. In: Advances in Neural Information Processing Systems. Vol. 35. NeurIPS. 2022, pp. 19099-19112 [Selected as Oral (7% of papers); publisher link; full; code; video; BibTeX]

@inproceedings{rubinstein2022unlabelled,
  title = {Unlabelled Sample Compression Schemes for Intersection-Closed Classes and Extremal Classes},
  author = {J. Hyam Rubinstein and Benjamin I. P. Rubinstein},
  booktitle = {Advances in Neural Information Processing Systems},
  series = {NeurIPS},
  year = {2022},
  pages = {13078--13090},
}

• Rubinstein, J. Hyam and Benjamin I. P. Rubinstein. “Unlabelled Sample Compression Schemes for Intersection-Closed Classes and Extremal Classes”. In: Advances in Neural Information Processing Systems. NeurIPS. 2022, pp. 13078-13090 [publisher link; full; video; BibTeX]

@inproceedings{jin2022are,
  title = {Are We There Yet? Timing and Floating-Point Attacks on Differential Privacy Systems},
  author = {Jiankai Jin and Eleanor McMurtry and Benjamin I. P. Rubinstein and Olga Ohrimenko},
  year = {2022},
  booktitle = {2022 IEEE Symposium on Security and Privacy (SP)},
  pages = {1547--1547},
}

• Jin, Jiankai, Eleanor McMurtry, Benjamin I. P. Rubinstein, and Olga Ohrimenko. “Are We There Yet? Timing and Floating-Point Attacks on Differential Privacy Systems”. In: 2022 IEEE Symposium on Security and Privacy (SP). 2022, pp. 1547-1547 [full; publisher link; BibTeX]

@article{perera2022hmab,
  title = {{HMAB}: Self-Driving Hierarchy of Bandits for Integrated Physical Database Design Tuning},
  author = {R. Malinga Perera and Bastian Oetomo and Benjamin I. P. Rubinstein and Renata Borovica-Gajic},
  year = {2022},
  journal = {Proceedings of the VLDB Endowment},
  publisher = {VLDB Endowment},
  volume = {16},
  number = {2},
  pages = {216--229},
}

• Perera, R. Malinga, Bastian Oetomo, Benjamin I. P. Rubinstein, and Renata Borovica-Gajic. “HMAB: Self-Driving Hierarchy of Bandits for Integrated Physical Database Design Tuning”. In: Proceedings of the VLDB Endowment 16.2 (2022), pp. 216-229 [publisher link; code; BibTeX]

@article{marchant2022hard,
  title = {Hard to Forget: Poisoning Attacks on Certified Machine Unlearning},
  author = {Neil G. Marchant and Benjamin I. P. Rubinstein and Scott Alfeld},
  year = {2022},
  journal = {Proceedings of the 36th AAAI Conference on Artificial Intelligence},
  series = {AAAI},
  volume = {36},
  number = {7},
  pages = {7691--7700},
}

• Marchant, Neil G., Benjamin I. P. Rubinstein, and Scott Alfeld. “Hard to Forget: Poisoning Attacks on Certified Machine Unlearning”. In: Proceedings of the 36th AAAI Conference on Artificial Intelligence. AAAI 36.7 (2022), pp. 7691-7700 [full; code; publisher link; BibTeX]

@article{edwards2020a,
  title = {A Graph Symmetrisation Bound on Channel Information Leakage under Blowfish Privacy},
  author = {Tobias Edwards and Benjamin I. P. Rubinstein and Zuhe Zhang and Sanming Zhou},
  journal = {IEEE Transactions on Information Theory},
  volume = {68},
  number = {1},
  pages = {538--548},
  year = {2022},
}

• Edwards, Tobias, Benjamin I. P. Rubinstein, Zuhe Zhang, and Sanming Zhou. “A Graph Symmetrisation Bound on Channel Information Leakage under Blowfish Privacy”. In: IEEE Transactions on Information Theory 68.1 (2022), pp. 538-548 [full; publisher link; BibTeX]

@inproceedings{wang2022a,
  title = {Measuring and Mitigating Name Biases in Neural Machine Translation},
  author = {Jun Wang and Benjamin I. P. Rubinstein and Trevor Cohn},
  booktitle = {Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)},
  series = {ACL},
  pages = {2576--2590},
  year = {2022},
}

• Wang, Jun, Benjamin I. P. Rubinstein, and Trevor Cohn. “Measuring and Mitigating Name Biases in Neural Machine Translation”. In: Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers). ACL. 2022, pp. 2576-2590 [publisher link; BibTeX]

@inproceedings{wang2022foiling,
  title = {Foiling Training-Time Attacks on Neural Machine Translation Systems},
  author = {Jun Wang and Xuanli He and Benjamin I. P. Rubinstein and Trevor Cohn},
  year = {2022},
  booktitle = {Findings of the Association for Computational Linguistics: EMNLP 2022},
  note = {Accepted},
}

• Wang, Jun, Xuanli He, Benjamin I. P. Rubinstein, and Trevor Cohn. “Foiling Training-Time Attacks on Neural Machine Translation Systems”. In: Findings of the Association for Computational Linguistics: EMNLP 2022. Accepted. 2022 [BibTeX]

@inproceedings{weera2021local,
  title = {Local Intrinsic Dimensionality Signals Adversarial Perturbations},
  author = {Sandamal Weerasinghe and Tansu Alpcan and Sarah M. Erfani and Christopher Leckie and Benjamin I. P. Rubinstein},
  booktitle = {2022 IEEE 61st Conference on Decision and Control},
  series = {CDC},
  note = {Accepted. In invited session Resilience, Security, and Privacy for Intelligent and Interconnected Systems},
  year = {2022},
}

• Weerasinghe, Sandamal, Tansu Alpcan, Sarah M. Erfani, Christopher Leckie, and Benjamin I. P. Rubinstein. “Local Intrinsic Dimensionality Signals Adversarial Perturbations”. In: 2022 IEEE 61st Conference on Decision and Control. CDC. Accepted. In invited session Resilience, Security, and Privacy for Intelligent and Interconnected Systems. 2022 [full; BibTeX]

@inproceedings{sun2022securing,
  title = {Securing Cyber-Physical Systems: Physics-Enhanced  Adversarial Learning for Autonomous Platoons},
  author = {Guoxin Sun and Tansu Alpcan and Benjamin I. P. Rubinstein and Seyit Camtepe},
  booktitle = {European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases},
  series = {ECML-PKDD},
  year = {2022},
  note = {Accepted},
}

• Sun, Guoxin, Tansu Alpcan, Benjamin I. P. Rubinstein, and Seyit Camtepe. “Securing Cyber-Physical Systems: Physics-Enhanced Adversarial Learning for Autonomous Platoons”. In: European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases. ECML-PKDD. Accepted. 2022 [code; BibTeX]

@inproceedings{liu2022state,
  title = {State Selection Algorithms and Their Impact on The Performance of Stateful Network Protocol Fuzzing},
  author = {Dongge Liu and Van-Thuan Pham and Gidon Ernst and Toby Murray and Benjamin I.P. Rubinstein},
  booktitle = {2022 IEEE International Conference on Software Analysis, Evolution and Reengineering},
  year = {2022},
  series = {SANER},
  note = {REproducibility Studies and NEgative Results (RENE) Track},
  pages = {720--730},
}

• Liu, Dongge, Van-Thuan Pham, Gidon Ernst, Toby Murray, and Benjamin I.P. Rubinstein. “State Selection Algorithms and Their Impact on The Performance of Stateful Network Protocol Fuzzing”. In: 2022 IEEE International Conference on Software Analysis, Evolution and Reengineering. SANER. REproducibility Studies and NEgative Results (RENE) Track. 2022, pp. 720-730 [full; publisher link; BibTeX]

@misc{bachfischer22testing,
  title = {Testing the Robustness of Learned Index Structures},
  author = {Matthias Bachfischer and Renata Borovica-Gajic and Benjamin I. P. Rubinstein},
  note = {arXiv:2207.11575 [cs.DB]},
  year = {2022},
  month = {July},
}

• Bachfischer, Matthias, Renata Borovica-Gajic, and Benjamin I. P. Rubinstein. Testing the Robustness of Learned Index Structures. arXiv:2207.11575 [cs.DB]. Jul. 2022 [PDF; BibTeX]

2021

@inproceedings{yang2021characterizing,
  title = {TRS: Transferability Reduced Ensemble via Promoting Gradient Diversity and Model Smoothness},
  year = {2021},
  author = {Zhuolin Yang and Linyi Li and Xiaojun Xu and Shiliang Zuo and Qian Chen and Pan Zhou and Benjamin Rubinstein and Ce Zhang and Bo Li},
  booktitle = {Advances in Neural Information Processing Systems},
  series = {NeurIPS},
  pages = {17642--17655},
  volume = {34},
}

• Yang, Zhuolin, Linyi Li, Xiaojun Xu, Shiliang Zuo, Qian Chen, Pan Zhou, Benjamin Rubinstein, Ce Zhang, and Bo Li. “TRS: Transferability Reduced Ensemble via Promoting Gradient Diversity and Model Smoothness”. In: Advances in Neural Information Processing Systems. Vol. 34. NeurIPS. 2021, pp. 17642-17655 [publisher link; full; BibTeX]

@inproceedings{marchant2021needle,
  title = {Needle in a Haystack: Label-Efficient Evaluation under Extreme Class Imbalance},
  author = {Neil G. Marchant and Benjamin I. P. Rubinstein},
  booktitle = {Proceedings of the 27th ACM SIGKDD International Conference on Knowledge Discovery \& Data Mining},
  series = {KDD},
  year = {2021},
  pages = {1180--1190},
}

• Marchant, Neil G. and Benjamin I. P. Rubinstein. “Needle in a Haystack: Label-Efficient Evaluation under Extreme Class Imbalance”. In: Proceedings of the 27th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining. KDD. 2021, pp. 1180-1190 [full; publisher link; code; video; BibTeX]

@inproceedings{xu2021a,
  title = {A Targeted Attack on Black-Box Neural Machine Translation with Parallel Data Poisoning},
  author = {Chang Xu and Jun Wang and Yuqing Tang and Francisco Guzm{\a'a}n and Benjamin I. P. Rubinstein and Trevor Cohn},
  booktitle = {Proceedings of the Web Conference 2021},
  series = {WWW},
  year = {2021},
  pages = {3638--3650},
}

• Xu, Chang, Jun Wang, Yuqing Tang, Francisco Guzmán, Benjamin I. P. Rubinstein, and Trevor Cohn. “A Targeted Attack on Black-Box Neural Machine Translation with Parallel Data Poisoning”. In: Proceedings of the Web Conference 2021. WWW. 2021, pp. 3638-3650 [PDF; publisher link; video; BibTeX]

@inproceedings{perera2020,
  title = {{DBA} bandits: Self-driving index tuning under ad-hoc, analytical workloads with safety guarantees},
  booktitle = {2021 IEEE 37th International Conference on Data Engineering},
  series = {ICDE},
  author = {R. Malinga Perera and Bastian Oetomo and Benjamin I. P. Rubinstein and Renata Borovica-Gajic},
  year = {2021},
  pages = {600--611},
}

• Perera, R. Malinga, Bastian Oetomo, Benjamin I. P. Rubinstein, and Renata Borovica-Gajic. “DBA bandits: Self-driving index tuning under ad-hoc, analytical workloads with safety guarantees”. In: 2021 IEEE 37th International Conference on Data Engineering. ICDE. 2021, pp. 600-611 [full; publisher link; video; BibTeX]

@article{marchant2020dblink,
  title = {d-blink: Distributed End-to-End Bayesian Entity Resolution},
  author = {Neil G. Marchant and Rebecca C. Steorts and Andee Kaplan and Benjamin I. P. Rubinstein and Daniel N. Elazar},
  journal = {Journal of Computational and Graphical Statistics},
  year = {2021},
  pages = {406--421},
  volume = {30},
  number = {2},
}

• Marchant, Neil G., Rebecca C. Steorts, Andee Kaplan, Benjamin I. P. Rubinstein, and Daniel N. Elazar. “d-blink: Distributed End-to-End Bayesian Entity Resolution”. In: Journal of Computational and Graphical Statistics 30.2 (2021), pp. 406-421 [full; code; publisher link; BibTeX]

@inproceedings{weerasinghe2021closing,
  title = {Closing the {BIG-LID}: An Effective Local Intrinsic Dimensionality Defense for Nonlinear Regression Poisoning},
  author = {Sandamal Weerasinghe and Benjamin I. P. Rubinstein and Tansu Alpcan and Sarah Erfani and Christopher Leckie and Tamas Abraham},
  booktitle = {Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence},
  series = {IJCAI},
  year = {2021},
  pages = {3176--3184},
}

• Weerasinghe, Sandamal, Benjamin I. P. Rubinstein, Tansu Alpcan, Sarah Erfani, Christopher Leckie, and Tamas Abraham. “Closing the BIG-LID: An Effective Local Intrinsic Dimensionality Defense for Nonlinear Regression Poisoning”. In: Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence. IJCAI. 2021, pp. 3176-3184 [publisher link; BibTeX]

@inproceedings{zhang2021improving,
  title = {Invertible Concept-Based Explanations for CNN Models with Non-Negative Concept Activation Vectors},
  author = {Ruihan Zhang and Prashan Madumal and Tim Miller and Kris Ehinger and Benjamin Rubinstein},
  booktitle = {Proceedings of the 35th AAAI Conference on Artificial Intelligence},
  series = {AAAI},
  year = {2021},
  pages = {11682--11690},
}

• Zhang, Ruihan, Prashan Madumal, Tim Miller, Kris Ehinger, and Benjamin Rubinstein. “Invertible Concept-Based Explanations for CNN Models with Non-Negative Concept Activation Vectors”. In: Proceedings of the 35th AAAI Conference on Artificial Intelligence. AAAI. 2021, pp. 11682-11690 [full; publisher link; code; BibTeX]

@inproceedings{oetomo2021cutting,
  title = {Cutting to the Chase with Warm-Start Contextual Bandits},
  author = {Bastian Oetomo and R. Malinga Perera and Renata Borovica-Gajic and Benjamin I. P. Rubinstein},
  year = {2021},
  series = {ICDM},
  booktitle = {2021 IEEE 21th International Conference on Data Mining},
  pages = {459--468},
}

• Oetomo, Bastian, R. Malinga Perera, Renata Borovica-Gajic, and Benjamin I. P. Rubinstein. “Cutting to the Chase with Warm-Start Contextual Bandits”. In: 2021 IEEE 21th International Conference on Data Mining. ICDM. 2021, pp. 459-468 [publisher link; BibTeX]

@inproceedings{Sun2021A,
  title = {A Communication Security Game on Switched Systems for Autonomous Vehicle Platoons},
  author = {Guoxin Sun and Tansu Alpcan and Benjamin I. P. Rubinstein and Seyit Camtepe},
  year = {2021},
  booktitle = {2021 60th IEEE Conference on Decision and Control},
  series = {CDC},
  pages = {2690--2695},
}

• Sun, Guoxin, Tansu Alpcan, Benjamin I. P. Rubinstein, and Seyit Camtepe. “A Communication Security Game on Switched Systems for Autonomous Vehicle Platoons”. In: 2021 60th IEEE Conference on Decision and Control. CDC. 2021, pp. 2690-2695 [full; publisher link; BibTeX]

@inproceedings{wang2021putting,
  title = {Putting words into the system's mouth: A targeted attack on neural machine translation using monolingual data poisoning},
  author = {Jun Wang and Chang Xu and Francisco Guzm{\a'a}n and Ahmed El-Kishky and Yuqing Tang and Benjamin I. P. Rubinstein and Trevor Cohn},
  year = {2021},
  booktitle = {Findings of the Association for Computational Linguistics: ACL-IJCNLP 2021},
  pages = {1463--1473},
}

• Wang, Jun, Chang Xu, Francisco Guzmán, Ahmed El-Kishky, Yuqing Tang, Benjamin I. P. Rubinstein, and Trevor Cohn. “Putting words into the system’s mouth: A targeted attack on neural machine translation using monolingual data poisoning”. In: Findings of the Association for Computational Linguistics: ACL-IJCNLP 2021. 2021, pp. 1463-1473 [full; code; publisher link; BibTeX]

@inproceedings{xu2021as,
  title = {As Easy as 1, 2, 3: Behavioural Testing of {NMT} Systems for Numerical Translation},
  author = {Jun Wang and Chang Xu and Francisco Guzm{\a'a}n and Ahmed El-Kishky and Yuqing Tang and Benjamin I. P. Rubinstein and Trevor Cohn},
  year = {2021},
  booktitle = {Findings of the Association for Computational Linguistics: ACL-IJCNLP 2021},
  pages = {4711--4717},
}

• Wang, Jun, Chang Xu, Francisco Guzmán, Ahmed El-Kishky, Yuqing Tang, Benjamin I. P. Rubinstein, and Trevor Cohn. “As Easy as 1, 2, 3: Behavioural Testing of NMT Systems for Numerical Translation”. In: Findings of the Association for Computational Linguistics: ACL-IJCNLP 2021. 2021, pp. 4711-4717 [full; code; publisher link; BibTeX]

@inproceedings{Sun2021strategic,
  title = {Strategic mitigation against wireless attacks on autonomous platoons},
  author = {Guoxin Sun and Tansu Alpcan and Benjamin I. P. Rubinstein and Seyit Camtepe},
  year = {2021},
  booktitle = {European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases},
  series = {ECML-PKDD},
  pages = {69--84},
}

• Sun, Guoxin, Tansu Alpcan, Benjamin I. P. Rubinstein, and Seyit Camtepe. “Strategic mitigation against wireless attacks on autonomous platoons”. In: European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases. ECML-PKDD. 2021, pp. 69-84 [code; publisher link; BibTeX]

@inproceedings{pham2021towards,
  title = {Towards Systematic and Dynamic Task Allocation for Collaborative Parallel Fuzzing},
  author = {Van-Thuan Pham and Manh-Dung Nguyen and Quang-Trung Ta and Toby Murray and Benjamin I. P. Rubinstein},
  year = {2021},
  booktitle = {Proceedings of the 36th IEEE/ACM International Conference on Automated Software Engineering},
  series = {ASE},
  note = {New Ideas and Emerging Results (NIER) track},
  pages = {1337--1341},
}

• Pham, Van-Thuan, Manh-Dung Nguyen, Quang-Trung Ta, Toby Murray, and Benjamin I. P. Rubinstein. “Towards Systematic and Dynamic Task Allocation for Collaborative Parallel Fuzzing”. In: Proceedings of the 36th IEEE/ACM International Conference on Automated Software Engineering. ASE. New Ideas and Emerging Results (NIER) track. 2021, pp. 1337-1341 [code; full; publisher link; BibTeX]

@inproceedings{xu2021mitigating,
  title = {Mitigating Data Poisoning in Text Classification with Differential Privacy},
  author = {Chang Xu and Jun Wang and Francisco Guzm{\a'a}n and Benjamin I. P. Rubinstein and Trevor Cohn},
  year = {2021},
  booktitle = {Findings of the Association for Computational Linguistics: EMNLP 2021},
  pages = {4348--4356},
}

• Xu, Chang, Jun Wang, Francisco Guzmán, Benjamin I. P. Rubinstein, and Trevor Cohn. “Mitigating Data Poisoning in Text Classification with Differential Privacy”. In: Findings of the Association for Computational Linguistics: EMNLP 2021. 2021, pp. 4348-4356 [publisher link; PDF; BibTeX]

@article{wang2021machine,
  title = {Machine Learning in Network Anomaly Detection: A Survey},
  author = {Song Wang and Juan Balarezo and Sithamparanathan Kandeepan and Akram Al-Hourani and Karina Gomez and Ben Rubinstein},
  year = {2021},
  journal = {IEEE Access},
  pages = {152379--152396},
  volume = {9},
}

• Wang, Song, Juan Balarezo, Sithamparanathan Kandeepan, Akram Al-Hourani, Karina Gomez, and Ben Rubinstein. “Machine Learning in Network Anomaly Detection: A Survey”. In: IEEE Access 9 (2021), pp. 152379-152396 [publisher link; BibTeX]

2020

@inproceedings{fish2020sampling,
  title = {Sampling Without Compromising Accuracy in Adaptive Data Analysis},
  author = {Benjamin Fish and Lev Reyzin and Benjamin I. P. Rubinstein},
  booktitle = {Proceedings of the 31st International Conference on Algorithmic Learning Theory},
  year = {2020},
  series = {ALT},
  organization = {PMLR},
  pages = {297--318},
}

• Fish, Benjamin, Lev Reyzin, and Benjamin I. P. Rubinstein. “Sampling Without Compromising Accuracy in Adaptive Data Analysis”. In: Proceedings of the 31st International Conference on Algorithmic Learning Theory. ALT. PMLR. 2020, pp. 297-318 [PDF; publisher link; full; BibTeX]

@article{leins2020tracking,
  title = {Tracking, tracing, trust: Contemplating mitigating the impact of COVID-19 through technological interventions},
  year = {2020},
  author = {Kobi Leins and Chris Culnane and Benjamin I. P. Rubinstein},
  journal = {Medical Journal of Australia},
  month = {July},
  volume = {213},
  number = {1},
  pages = {6--8},
}

• Leins, Kobi, Chris Culnane, and Benjamin I. P. Rubinstein. “Tracking, tracing, trust: Contemplating mitigating the impact of COVID-19 through technological interventions”. In: Medical Journal of Australia 213.1 (Jul. 2020), pp. 6-8 [publisher link; BibTeX]

@article{Zhou2020early,
  title = {Early identification of an impending rockslide location via a spatially-aided Gaussian mixture model},
  year = {2020},
  author = {Shuo Zhou and Howard Bondell and Antoinette Tordesillas and Benjamin I. P. Rubinstein and James Bailey},
  journal = {Annals of Applied Statistics},
  volume = {14},
  number = {2},
  pages = {977-992},
}

• Zhou, Shuo, Howard Bondell, Antoinette Tordesillas, Benjamin I. P. Rubinstein, and James Bailey. “Early identification of an impending rockslide location via a spatially-aided Gaussian mixture model”. In: Annals of Applied Statistics 14.2 (2020), pp. 977-992 [PDF; publisher link; BibTeX]

@misc{culnane2020a,
  title = {Not fit for Purpose: A critical analysis of the 'Five Safes'},
  author = {Chris Culnane and Benjamin I. P. Rubinstein and David Watts},
  note = {arXiv:2011.02142 [cs.CR]},
  year = {2020},
  month = {Nov},
}

• Culnane, Chris, Benjamin I. P. Rubinstein, and David Watts. Not fit for Purpose: A critical analysis of the ‘Five Safes’. arXiv:2011.02142 [cs.CR]. Nov. 2020 [PDF; BibTeX]

@inproceedings{liu2020legionb,
  title = {Legion: Best-First Concolic Testing},
  year = {2020},
  author = {Dongge Liu and Gidon Ernst and Toby Murray and Benjamin I. P. Rubinstein},
  booktitle = {2020 35th IEEE/ACM International Conference on Automated Software Engineering},
  series = {ASE},
  pages = {54--65},
}

• Liu, Dongge, Gidon Ernst, Toby Murray, and Benjamin I. P. Rubinstein. “Legion: Best-First Concolic Testing”. In: 2020 35th IEEE/ACM International Conference on Automated Software Engineering. ASE. 2020, pp. 54-65 [code; PDF; BibTeX]

@inproceedings{liu2020legion,
  title = {Legion: Best-First Concolic Testing},
  year = {2020},
  author = {Dongge Liu and Gidon Ernst and Toby Murray and Benjamin I. P. Rubinstein},
  booktitle = {Proceedings of the 23rd International Conference on Fundamental Approaches to Software Engineering},
  series = {FASE},
  note = {Test-Comp session},
  pages = {545--549},
}

• Liu, Dongge, Gidon Ernst, Toby Murray, and Benjamin I. P. Rubinstein. “Legion: Best-First Concolic Testing”. In: Proceedings of the 23rd International Conference on Fundamental Approaches to Software Engineering. FASE. Test-Comp session. 2020, pp. 545-549 [code; publisher link; BibTeX]

@inproceedings{setiawan2020function,
  title = {Function Interpolation for Learned Index Structures},
  year = {2020},
  author = {Naufal Fikri Setiawan and Benjamin I. P. Rubinstein and Renata Borovica-Gajic},
  booktitle = {Databases Theory and Applications},
  series = {ADC},
  note = {31st Australasian Database Conference},
  pages = {68--80},
}

• Setiawan, Naufal Fikri, Benjamin I. P. Rubinstein, and Renata Borovica-Gajic. “Function Interpolation for Learned Index Structures”. In: Databases Theory and Applications. ADC. 31st Australasian Database Conference. 2020, pp. 68-80 [publisher link; Best Student Paper Honorable Mention; BibTeX]

@misc{yang2020characterizing,
  title = {Characterizing Adversarial Transferability via Gradient Orthogonality and Smoothness},
  year = {2020},
  author = {Zhuolin Yang and Linyi Li and Xiaojun Xu and Shiliang Zuo and Qian Chen and Benjamin Rubinstein and Ce Zhang and Bo Li},
  note = {Appeared at ICML2020 Workshop on Uncertainty & Robustness in Deep Learning},
}

• Yang, Zhuolin, Linyi Li, Xiaojun Xu, Shiliang Zuo, Qian Chen, Benjamin Rubinstein, Ce Zhang, and Bo Li. Characterizing Adversarial Transferability via Gradient Orthogonality and Smoothness. Appeared at ICML2020 Workshop on Uncertainty & Robustness in Deep Learning. 2020 [PDF; BibTeX]

@inproceedings{roohi2020assessing,
  title = {Assessing Centrality Without Knowing Connections},
  year = {2020},
  author = {Leyla Roohi and Benjamin I. P. Rubinstein and Vanessa Teague},
  booktitle = {24th Pacific-Asia Conference on Knowledge Discovery and Data Mining},
  series = {PAKDD},
  pages = {152--163},
}

• Roohi, Leyla, Benjamin I. P. Rubinstein, and Vanessa Teague. “Assessing Centrality Without Knowing Connections”. In: 24th Pacific-Asia Conference on Knowledge Discovery and Data Mining. PAKDD. 2020, pp. 152-163 [full; publisher link; BibTeX]

@inproceedings{han2020adversarial,
  title = {Adversarial Reinforcement Learning under Partial Observability in Autonomous Computer Network Defence},
  year = {2020},
  author = {Yi Han and David Hubczenko and Paul Montague and Olivier {De Vel} and Tamas Abraham and Benjamin I. P. Rubinstein and Christopher Leckie and Tansu Alpcan and Sarah Erfani},
  booktitle = {2020 International Joint Conference on Neural Networks},
  series = {IJCNN},
  pages = {1--8},
}

• Han, Yi, David Hubczenko, Paul Montague, Olivier De Vel, Tamas Abraham, Benjamin I. P. Rubinstein, Christopher Leckie, Tansu Alpcan, and Sarah Erfani. “Adversarial Reinforcement Learning under Partial Observability in Autonomous Computer Network Defence”. In: 2020 International Joint Conference on Neural Networks. IJCNN. 2020, pp. 1-8 [full; publisher link; BibTeX]

@misc{gelbhart2020discrete,
  title = {Discrete Few-Shot Learning for Pan Privacy},
  author = {Roei Gelbhart and Benjamin I. P. Rubinstein},
  note = {arXiv:2006.13120 [cs.LG]},
  year = {2020},
  month = {Jun},
}

• Gelbhart, Roei and Benjamin I. P. Rubinstein. Discrete Few-Shot Learning for Pan Privacy. arXiv:2006.13120 [cs.LG]. Jun. 2020 [PDF; BibTeX]

2019

@inproceedings{li2019exploiting,
  title = {Exploiting Worker Correlation for Label Aggregation in Crowdsourcing},
  author = {Yuan Li and Benjamin I. P. Rubinstein and Trevor Cohn},
  year = {2019},
  booktitle = {Proceedings of the 36th International Conference on Machine Learning},
  series = {ICML},
  pages = {3886--3895},
  publisher = {PMLR},
}

• Li, Yuan, Benjamin I. P. Rubinstein, and Trevor Cohn. “Exploiting Worker Correlation for Label Aggregation in Crowdsourcing”. In: Proceedings of the 36th International Conference on Machine Learning. ICML. PMLR, 2019, pp. 3886-3895 [PDF; code; BibTeX]

@inproceedings{li2019truth,
  title = {Truth inference at scale: {A} {B}ayesian model for adjudicating highly redundant crowd annotations},
  author = {Yuan Li and Benjamin I. P. Rubinstein and Trevor Cohn},
  year = {2019},
  booktitle = {Proceedings of the Web Conference 2019},
  series = {WWW},
  pages = {1028--1038},
}

• Li, Yuan, Benjamin I. P. Rubinstein, and Trevor Cohn. “Truth inference at scale: A Bayesian model for adjudicating highly redundant crowd annotations”. In: Proceedings of the Web Conference 2019. WWW. 2019, pp. 1028-1038 [full; publisher link; BibTeX]

@inproceedings{roohi2019differentiallyprivate,
  title = {Differentially-Private Two-Party Egocentric Betweenness Centrality},
  author = {Leyla Roohi and Benjamin I. P. Rubinstein and Vanessa Teague},
  year = {2019},
  booktitle = {The 38th Annual IEEE International Conference on Computer Communications},
  series = {INFOCOM},
  pages = {2233--2241},
}

• Roohi, Leyla, Benjamin I. P. Rubinstein, and Vanessa Teague. “Differentially-Private Two-Party Egocentric Betweenness Centrality”. In: The 38th Annual IEEE International Conference on Computer Communications. INFOCOM. 2019, pp. 2233-2241 [full; publisher link; BibTeX]

@inproceedings{alfeld2019attacking,
  title = {Attacking Data Transforming Learners at Training Time},
  author = {Scott Alfeld and Ara Vartanian and Lucas Newman-Johnson and Benjamin I.P Rubinstein},
  booktitle = {Proceedings of the 33rd AAAI Conference on Artificial Intelligence},
  series = {AAAI},
  pages = {3167--3174},
  year = {2019},
}

• Alfeld, Scott, Ara Vartanian, Lucas Newman-Johnson, and Benjamin I.P Rubinstein. “Attacking Data Transforming Learners at Training Time”. In: Proceedings of the 33rd AAAI Conference on Artificial Intelligence. AAAI. 2019, pp. 3167-3174 [publisher link; BibTeX]

@book{joseph2019adversarial,
  title = {Adversarial Machine Learning},
  year = {2019},
  author = {Anthony D. Joseph and Blaine Nelson and Benjamin I. P. Rubinstein and J. D. Tygar},
  publisher = {Cambridge University Press},
}

• Joseph, Anthony D., Blaine Nelson, Benjamin I. P. Rubinstein, and J. D. Tygar. Adversarial Machine Learning. Cambridge University Press, 2019 [publisher link; BibTeX]

@incollection{rubinstein2019data,
  title = {Data Security and AI},
  author = {Benjamin I. P. Rubinstein},
  booktitle = {Closer to the machine: {T}echnical, social, and legal aspects of {AI}},
  editor = {Cliff Betram and Asher Gibson and Adriana Nugent},
  pages = {105--119},
  year = {2019},
  publisher = {{Office of the Victorian Information Commissioner}},
}

• Rubinstein, Benjamin I. P. “Data Security and AI”. In: Closer to the machine: Technical, social, and legal aspects of AI. Ed. by Cliff Betram, Asher Gibson and Adriana Nugent. Office of the Victorian Information Commissioner, 2019, pp. 105-119 [PDF; BibTeX]

@misc{culnane2019stop,
  title = {Stop the Open Data Bus, We Want to Get Off},
  author = {Chris Culnane and Benjamin I. P. Rubinstein and Vanessa Teague},
  eprint = {1908.05004},
  year = {2019},
  month = {Aug},
  archiveprefix = {arXiv},
  primaryclass = {cs.CR},
}

• Culnane, Chris, Benjamin I. P. Rubinstein, and Vanessa Teague. Stop the Open Data Bus, We Want to Get Off. Aug. 2019. arXiv: 1908.05004 [cs.CR]. [PDF; pop article; BibTeX]

@misc{oetomo2019a,
  title = {A Note on Bounding Regret of the C$^2$UCB Contextual Combinatorial Bandit},
  author = {Bastian Oetomo and Malinga Perera and Renata Borovica-Gajic and Benjamin I. P. Rubinstein},
  eprint = {1902.07500},
  year = {2019},
  month = {Feb},
  archiveprefix = {arXiv},
  primaryclass = {cs.LG},
}

• Oetomo, Bastian, Malinga Perera, Renata Borovica-Gajic, and Benjamin I. P. Rubinstein. A Note on Bounding Regret of the C\(^2\)UCB Contextual Combinatorial Bandit. Feb. 2019. arXiv: 1902.07500 [cs.LG]. [PDF; BibTeX]

2018

@inproceedings{fanaeepour2018histogramming,
  title = {Histogramming Privately Ever After: Differentially-Private Data-Dependent Error Bound Optimisation},
  author = {Maryam Fanaeepour and Benjamin I. P. Rubinstein},
  booktitle = {2018 IEEE 34th International Conference on Data Engineering},
  series = {ICDE},
  year = {2018},
  month = {Apr},
  pages = {1204--1207},
  organization = {IEEE},
}

• Fanaeepour, Maryam and Benjamin I. P. Rubinstein. “Histogramming Privately Ever After: Differentially-Private Data-Dependent Error Bound Optimisation”. In: 2018 IEEE 34th International Conference on Data Engineering. ICDE. IEEE. Apr. 2018, pp. 1204-1207 [full; publisher link; BibTeX]

@inproceedings{han2018reinforcement,
  title = {Reinforcement Learning for Autonomous Defence in Software-Defined Networking},
  author = {Yi Han and Benjamin I. P. Rubinstein and Tamas Abraham and Tansu Alpcan and Olivier {De Vel} and Sarah Erfani and David Hubczenko and Christopher Leckie and Paul Montague},
  booktitle = {9th International Conference on Decision and Game Theory for Security},
  series = {GameSec},
  pages = {145--165},
  year = {2018},
  organization = {Springer},
}

• Han, Yi, Benjamin I. P. Rubinstein, Tamas Abraham, Tansu Alpcan, Olivier De Vel, Sarah Erfani, David Hubczenko, Christopher Leckie, and Paul Montague. “Reinforcement Learning for Autonomous Defence in Software-Defined Networking”. In: 9th International Conference on Decision and Game Theory for Security. GameSec. Springer. 2018, pp. 145-165 [full; publisher link; BibTeX]

@article{fanaeepour2018differentially,
  title = {Differentially private counting of users' spatial regions},
  author = {Maryam Fanaeepour and Benjamin I. P. Rubinstein},
  journal = {Knowledge and Information Systems},
  pages = {1--28},
  year = {2018},
  month = {Jan},
  volume = {54},
  number = {1},
  publisher = {Springer London},
}

• Fanaeepour, Maryam and Benjamin I. P. Rubinstein. “Differentially private counting of users’ spatial regions”. In: Knowledge and Information Systems 54.1 (Jan. 2018), pp. 1-28 [publisher link; BibTeX]

@article{lyu2018ppfa,
  author = {Lingjuan Lyu and Karthik Nandakumar and Benjamin I. P. Rubinstein and Jiong Jin and Justin Bedo and Marimuthu Palaniswami},
  title = {{PPFA}: Privacy-Preserving Fog-enabled Aggregation in Smart Grid},
  journal = {IEEE Transactions on Industrial Informatics},
  month = {Aug},
  year = {2018},
  volume = {14},
  number = {8},
  pages = {3733-3744},
}

• Lyu, Lingjuan, Karthik Nandakumar, Benjamin I. P. Rubinstein, Jiong Jin, Justin Bedo, and Marimuthu Palaniswami. “PPFA: Privacy-Preserving Fog-enabled Aggregation in Smart Grid”. In: IEEE Transactions on Industrial Informatics 14.8 (Aug. 2018), pp. 3733-3744 [publisher link; BibTeX]

@misc{culnane2018options,
  title = {Options for encoding names for data linking at the Australian Bureau of Statistics},
  author = {Chris Culnane and Benjamin I. P. Rubinstein and Vanessa Teague},
  eprint = {1802.07975},
  year = {2018},
  month = {Feb},
  archiveprefix = {arXiv},
  primaryclass = {cs.CR},
}

• Culnane, Chris, Benjamin I. P. Rubinstein, and Vanessa Teague. Options for encoding names for data linking at the Australian Bureau of Statistics. Feb. 2018. arXiv: 1802.07975 [cs.CR]. [PDF; BibTeX]

@inproceedings{aye2018fast,
  author = {Zay Maung Maung Aye and Kotagiri Ramamohanaro and Benjamin I. P. Rubinstein},
  title = {Fast Manifold Landmarking with Locality Sensitive Hashing},
  booktitle = {22nd Pacific-Asia Conference on Knowledge Discovery and Data Mining},
  series = {PAKDD},
  month = {Feb},
  year = {2018},
  pages = {452--464},
}

• Aye, Zay Maung Maung, Kotagiri Ramamohanaro, and Benjamin I. P. Rubinstein. “Fast Manifold Landmarking with Locality Sensitive Hashing”. In: 22nd Pacific-Asia Conference on Knowledge Discovery and Data Mining. PAKDD. Feb. 2018, pp. 452-464 [publisher link; BibTeX]

@inproceedings{han2018adequacy,
  title = {Adequacy of the Gradient-Descent Method for Classifier Evasion Attacks},
  author = {Yi Han and Benjamin I. P. Rubinstein},
  booktitle = {AAAI-18 Workshop on Artificial Intelligence for Cyber Security},
  series = {AICS},
  year = {2018},
  pages = {237--244},
  month = {Jan},
}

• Han, Yi and Benjamin I. P. Rubinstein. “Adequacy of the Gradient-Descent Method for Classifier Evasion Attacks”. In: AAAI-18 Workshop on Artificial Intelligence for Cyber Security. AICS. Jan. 2018, pp. 237-244 [PDF; BibTeX]

2017

@article{marchant2017in,
  title = {In Search of an Entity Resolution {OASIS}: Optimal Asymptotic Sequential Importance Sampling},
  author = {Neil G. Marchant and Benjamin I. P. Rubinstein},
  journal = {Proceedings of the VLDB Endowment},
  volume = {10},
  number = {11},
  pages = {1322--1333},
  year = {2017},
  month = {Feb},
  publisher = {VLDB Endowment},
}

• Marchant, Neil G. and Benjamin I. P. Rubinstein. “In Search of an Entity Resolution OASIS: Optimal Asymptotic Sequential Importance Sampling”. In: Proceedings of the VLDB Endowment 10.11 (Feb. 2017), pp. 1322-1333 [PDF; full; code; BibTeX]

@inproceedings{rubinstein2017painfree,
  title = {Pain-Free Random Differential Privacy with Sensitivity Sampling},
  author = {Benjamin I. P. Rubinstein and Francesco Alda},
  booktitle = {Proceedings of the 34th International Conference on Machine Learning},
  series = {ICML},
  pages = {2950--2959},
  year = {2017},
  month = {May},
  organization = {PMLR},
}

• Rubinstein, Benjamin I. P. and Francesco Alda. “Pain-Free Random Differential Privacy with Sensitivity Sampling”. In: Proceedings of the 34th International Conference on Machine Learning. ICML. PMLR. May. 2017, pp. 2950-2959 [PDF; full; code; BibTeX]

@inproceedings{alda2017the,
  title = {The Bernstein mechanism: Function release under differential privacy},
  author = {Francesco Alda and Benjamin I. P. Rubinstein},
  booktitle = {Proceedings of the 31st AAAI Conference on Artificial Intelligence},
  series = {AAAI},
  year = {2017},
  month = {Feb},
  pages = {1705--1711},
}

• Alda, Francesco and Benjamin I. P. Rubinstein. “The Bernstein mechanism: Function release under differential privacy”. In: Proceedings of the 31st AAAI Conference on Artificial Intelligence. AAAI. Feb. 2017, pp. 1705-1711 [PDF; full; code; BibTeX]

@article{dimitrakakis2017differential,
  title = {Differential privacy for {B}ayesian inference through posterior sampling},
  author = {Christos Dimitrakakis and Blaine Nelson and Zuhe Zhang and Aikateirni Mitrokotsa and Benjamin I. P. Rubinstein},
  journal = {Journal of Machine Learning Research},
  volume = {18},
  number = {11},
  pages = {1--39},
  year = {2017},
  month = {Mar},
}

• Dimitrakakis, Christos, Blaine Nelson, Zuhe Zhang, Aikateirni Mitrokotsa, and Benjamin I. P. Rubinstein. “Differential privacy for Bayesian inference through posterior sampling”. In: Journal of Machine Learning Research 18.11 (Mar. 2017), pp. 1-39 [PDF; BibTeX]

@article{lau2017machinelearning,
  title = {Machine-learning algorithms predict graft failure after liver transplantation},
  author = {Lawrence Lau and Yamuna Kankanige and Benjamin Rubinstein and Robert Jones and Christopher Christophi and Vijayaragavan Muralidharan and James Bailey},
  journal = {Transplantation},
  volume = {101},
  number = {4},
  pages = {125--132},
  year = {2017},
  month = {Apr},
  publisher = {LWW},
}

• Lau, Lawrence, Yamuna Kankanige, Benjamin Rubinstein, Robert Jones, Christopher Christophi, Vijayaragavan Muralidharan, and James Bailey. “Machine-learning algorithms predict graft failure after liver transplantation”. In: Transplantation 101.4 (Apr. 2017), pp. 125-132 [publisher link; BibTeX]

@book{verkade2017misconceptions,
  title = {Misconceptions as a trigger for enhancing student learning in higher education: A handbook for educators},
  author = {Heather Verkade and Terrence D. Mulhern and Jason M. Lodge and Kristine Elliott and Simon Cropper and Benjamin I. P. Rubinstein and Allen Espinosa and Michelle Livett and Laura Dooley and Sarah Frankland and Raoul Mulder},
  year = {2017},
  publisher = {Published by The University of Melbourne},
}

• Verkade, Heather, Terrence D. Mulhern, Jason M. Lodge, Kristine Elliott, Simon Cropper, Benjamin I. P. Rubinstein, Allen Espinosa, Michelle Livett, Laura Dooley, Sarah Frankland, and Raoul Mulder. Misconceptions as a trigger for enhancing student learning in higher education: A handbook for educators. Published by The University of Melbourne, 2017. ISBN: 978 0 7340 5410 4 [PDF; BibTeX]

@inproceedings{liu2017estorm,
  title = {E-storm: Replication-based state management in distributed stream processing systems},
  author = {Xunyun Liu and Aaron Harwood and Shanika Karunasekera and Benjamin Rubinstein and Rajkumar Buyya},
  booktitle = {46th International Conference on Parallel Processing},
  series = {ICPP},
  pages = {571--580},
  year = {2017},
  organization = {IEEE},
}

• Liu, Xunyun, Aaron Harwood, Shanika Karunasekera, Benjamin Rubinstein, and Rajkumar Buyya. “E-storm: Replication-based state management in distributed stream processing systems”. In: 46th International Conference on Parallel Processing. ICPP. IEEE. 2017, pp. 571-580 [PDF; publisher link; BibTeX]

@misc{culnane2017privacy,
  title = {Privacy Assessment of De-identified Opal Data: A report for Transport for NSW},
  author = {Chris Culnane and Benjamin I. P. Rubinstein and Vanessa Teague},
  eprint = {1704.08547},
  year = {2017},
  month = {May},
  archiveprefix = {arXiv},
  primaryclass = {cs.CR},
}

• Culnane, Chris, Benjamin I. P. Rubinstein, and Vanessa Teague. Privacy Assessment of De-identified Opal Data: A report for Transport for NSW. May. 2017. arXiv: 1704.08547 [cs.CR]. [PDF; BibTeX]

@misc{culnane2017vulnerabilities,
  title = {Vulnerabilities in the use of similarity tables in combination with pseudonymisation to preserve data privacy in the UK Office for National Statistics' Privacy-Preserving Record Linkage},
  author = {Chris Culnane and Benjamin I. P. Rubinstein and Vanessa Teague},
  eprint = {1712.00871},
  year = {2017},
  archiveprefix = {arXiv},
  primaryclass = {cs.CR},
}

• Culnane, Chris, Benjamin I. P. Rubinstein, and Vanessa Teague. Vulnerabilities in the use of similarity tables in combination with pseudonymisation to preserve data privacy in the UK Office for National Statistics’ Privacy-Preserving Record Linkage. 2017. arXiv: 1712.00871 [cs.CR]. [PDF; pop article; BibTeX]

@misc{culnane2017health,
  title = {Health Data in an Open World},
  author = {Chris Culnane and Benjamin I. P. Rubinstein and Vanessa Teague},
  eprint = {1712.05627},
  year = {2017},
  month = {Dec},
  archiveprefix = {arXiv},
  primaryclass = {cs.CY},
}

• Culnane, Chris, Benjamin I. P. Rubinstein, and Vanessa Teague. Health Data in an Open World. Dec. 2017. arXiv: 1712.05627 [cs.CY]. [PDF; pop article; BibTeX]

@inproceedings{verkade2017exploring,
  title = {Exploring misconceptions as a trigger for enhancing student learning},
  author = {Heather Verkade and Jason M. Lodge and Kristine Elliott and Terrence D. Mulhern and Allen A. Espinosa and Simon J. Cropper and Benjamin I. P. Rubinstein},
  booktitle = {Higher Education Research and Development Society of Australasia},
  series = {HERDSA},
  year = {2017},
  month = {Apr},
  pages = {392--401},
}

• Verkade, Heather, Jason M. Lodge, Kristine Elliott, Terrence D. Mulhern, Allen A. Espinosa, Simon J. Cropper, and Benjamin I. P. Rubinstein. “Exploring misconceptions as a trigger for enhancing student learning”. In: Higher Education Research and Development Society of Australasia. HERDSA. Apr. 2017, pp. 392-401 [PDF; publisher link; BibTeX]

2016

@inproceedings{zhang2016on,
  title = {On the differential privacy of {B}ayesian inference},
  author = {Zuhe Zhang and Benjamin I. P. Rubinstein and Christos Dimitrakakis},
  booktitle = {Proceedings of the 30th AAAI Conference on Artificial Intelligence},
  series = {AAAI},
  pages = {2365--2371},
  year = {2016},
  month = {Feb},
}

• Zhang, Zuhe, Benjamin I. P. Rubinstein, and Christos Dimitrakakis. “On the differential privacy of Bayesian inference”. In: Proceedings of the 30th AAAI Conference on Artificial Intelligence. AAAI. Feb. 2016, pp. 2365-2371 [PDF; full; BibTeX]

@inproceedings{he2016moocs,
  title = {{MOOCs} meet measurement theory: A topic-modelling approach},
  author = {Jiazhen He and Benjamin I. P. Rubinstein and James Bailey and Rui Zhang and Sandra Milligan and Jeffrey Chan},
  booktitle = {Proceedings of the 30th AAAI Conference on Artificial Intelligence},
  pages = {1195--1201},
  series = {AAAI},
  year = {2016},
  month = {Feb},
}

• He, Jiazhen, Benjamin I. P. Rubinstein, James Bailey, Rui Zhang, Sandra Milligan, and Jeffrey Chan. “MOOCs meet measurement theory: A topic-modelling approach”. In: Proceedings of the 30th AAAI Conference on Artificial Intelligence. AAAI. Feb. 2016, pp. 1195-1201 [PDF; full; BibTeX]

@inproceedings{fanaeepour2016beyond,
  title = {Beyond points and paths: counting private bodies},
  author = {Maryam Fanaeepour and Benjamin I. P. Rubinstein},
  booktitle = {2016 IEEE 16th International Conference on Data Mining},
  series = {ICDM},
  pages = {131--140},
  year = {2016},
  month = {Dec},
  organization = {IEEE},
}

• Fanaeepour, Maryam and Benjamin I. P. Rubinstein. “Beyond points and paths: counting private bodies”. In: 2016 IEEE 16th International Conference on Data Mining. ICDM. IEEE. Dec. 2016, pp. 131-140 [full; publisher link; Winner, WiE Best Postgraduate Student Paper, IEEE Australia Council; BibTeX]

@inproceedings{alpcan2016largescale,
  title = {Large-scale strategic games and adversarial machine learning},
  author = {Tansu Alpcan and Benjamin I. P. Rubinstein and Christopher Leckie},
  booktitle = {2016 IEEE 55th Conference on Decision and Control},
  series = {CDC},
  pages = {4420--4426},
  year = {2016},
  month = {Dec},
  organization = {IEEE},
}

• Alpcan, Tansu, Benjamin I. P. Rubinstein, and Christopher Leckie. “Large-scale strategic games and adversarial machine learning”. In: 2016 IEEE 55th Conference on Decision and Control. CDC. IEEE. Dec. 2016, pp. 4420-4426 [full; publisher link; BibTeX]

@article{han2016a,
  title = {A game theoretical approach to defend against co-resident attacks in cloud computing: Preventing co-residence using semi-supervised learning},
  author = {Yi Han and Tansu Alpcan and Jeffrey Chan and Christopher Leckie and Benjamin I. P. Rubinstein},
  journal = {IEEE Transactions on information Forensics and Security},
  volume = {11},
  number = {3},
  pages = {556--570},
  year = {2016},
  month = {Mar},
  publisher = {IEEE},
}

• Han, Yi, Tansu Alpcan, Jeffrey Chan, Christopher Leckie, and Benjamin I. P. Rubinstein. “A game theoretical approach to defend against co-resident attacks in cloud computing: Preventing co-residence using semi-supervised learning”. In: IEEE Transactions on information Forensics and Security 11.3 (Mar. 2016), pp. 556-570 [publisher link; BibTeX]

@inproceedings{aye2016large,
  title = {Large Scale Metric learning},
  author = {Zay Maung Maung Aye and Kotagiri Ramamohanarao and Benjamin I. P. Rubinstein},
  booktitle = {2016 International Joint Conference on Neural Networks},
  series = {IJCNN},
  pages = {1442--1449},
  year = {2016},
  month = {Jul},
  organization = {IEEE},
}

• Aye, Zay Maung Maung, Kotagiri Ramamohanarao, and Benjamin I. P. Rubinstein. “Large Scale Metric learning”. In: 2016 International Joint Conference on Neural Networks. IJCNN. IEEE. Jul. 2016, pp. 1442-1449 [publisher link; BibTeX]

@inproceedings{sanchez2016fast,
  title = {Fast trajectory clustering using Hashing methods},
  author = {Ivan Sanchez and Zay Maung Maung Aye and Benjamin I. P. Rubinstein and Kotagiri Ramamohanarao},
  booktitle = {2016 International Joint Conference on Neural Networks},
  series = {IJCNN},
  pages = {3689--3696},
  year = {2016},
  month = {Jul},
  organization = {IEEE},
}

• Sanchez, Ivan, Zay Maung Maung Aye, Benjamin I. P. Rubinstein, and Kotagiri Ramamohanarao. “Fast trajectory clustering using Hashing methods”. In: 2016 International Joint Conference on Neural Networks. IJCNN. IEEE. Jul. 2016, pp. 3689-3696 [publisher link; BibTeX]

@inproceedings{milligan2016validity,
  title = {Validity: a framework for cross-disciplinary collaboration in mining indicators of learning from {MOOC} forums},
  author = {Sandra Milligan and Jiazhen He and James Bailey and Rui Zhang and Benjamin I. P. Rubinstein},
  booktitle = {Proceedings of the Sixth International Conference on Learning Analytics \& Knowledge},
  series = {LAK},
  pages = {546--547},
  year = {2016},
  month = {Apr},
  organization = {ACM},
}

• Milligan, Sandra, Jiazhen He, James Bailey, Rui Zhang, and Benjamin I. P. Rubinstein. “Validity: a framework for cross-disciplinary collaboration in mining indicators of learning from MOOC forums”. In: Proceedings of the Sixth International Conference on Learning Analytics & Knowledge. LAK. ACM. Apr. 2016, pp. 546-547 [publisher link; BibTeX]

@misc{he2016topicresponse,
  title = {{TopicResponse}: A Marriage of Topic Modelling and Rasch Modelling for Automatic Measurement in {MOOCs}},
  author = {Jiazhen He and Benjamin I. P. Rubinstein and James Bailey and Rui Zhang and Sandra Milligan},
  eprint = {1607.08720},
  year = {2016},
  archiveprefix = {arXiv},
  primaryclass = {cs.LG},
}

• He, Jiazhen, Benjamin I. P. Rubinstein, James Bailey, Rui Zhang, and Sandra Milligan. TopicResponse: A Marriage of Topic Modelling and Rasch Modelling for Automatic Measurement in MOOCs. 2016. arXiv: 1607.08720 [cs.LG]. [PDF; code; BibTeX]

2015

@inproceedings{he2015identifying,
  title = {Identifying At-Risk Students in Massive Open Online Courses},
  author = {Jiazhen He and James Bailey and Benjamin I. P. Rubinstein and Rui Zhang},
  booktitle = {Proceedings of the 29th AAAI Conference on Artificial Intelligence},
  series = {AAAI},
  pages = {1749--1755},
  year = {2015},
}

• He, Jiazhen, James Bailey, Benjamin I. P. Rubinstein, and Rui Zhang. “Identifying At-Risk Students in Massive Open Online Courses”. In: Proceedings of the 29th AAAI Conference on Artificial Intelligence. AAAI. 2015, pp. 1749-1755 [PDF; BibTeX]

@inproceedings{lim2015submerge,
  title = {Sub-Merge: Diving Down to the Attribute-Value Level in Statistical Schema Matching.},
  author = {Zhe Lim and Benjamin I. P. Rubinstein},
  booktitle = {Proceedings of the 29th AAAI Conference on Artificial Intelligence},
  series = {AAAI},
  pages = {1791--1797},
  year = {2015},
  month = {Jan},
}

• Lim, Zhe and Benjamin I. P. Rubinstein. “Sub-Merge: Diving Down to the Attribute-Value Level in Statistical Schema Matching.” In: Proceedings of the 29th AAAI Conference on Artificial Intelligence. AAAI. Jan. 2015, pp. 1791-1797 [PDF; dataset; BibTeX]

@article{zhang2015principled,
  title = {Principled graph matching algorithms for integrating multiple data sources},
  author = {Duo Zhang and Benjamin I. P. Rubinstein and Jim Gemmell},
  journal = {IEEE Transactions on Knowledge and Data Engineering},
  volume = {27},
  number = {10},
  pages = {2784--2796},
  year = {2015},
  month = {Apr},
  publisher = {IEEE},
}

• Zhang, Duo, Benjamin I. P. Rubinstein, and Jim Gemmell. “Principled graph matching algorithms for integrating multiple data sources”. In: IEEE Transactions on Knowledge and Data Engineering 27.10 (Apr. 2015), pp. 2784-2796 [full; publisher link; BibTeX]

@incollection{rubinstein2015bounding,
  title = {Bounding embeddings of {VC} classes into maximum classes},
  author = {J. Hyam Rubinstein and Benjamin I. P. Rubinstein and Peter L. Bartlett},
  booktitle = {Measures of Complexity: Festschrift of Alexey Chervonenkis},
  editor = {V. Vovk and H. Papadopoulos and A. Gammerman},
  pages = {303--325},
  year = {2015},
  publisher = {Springer},
}

• Rubinstein, J. Hyam, Benjamin I. P. Rubinstein, and Peter L. Bartlett. “Bounding embeddings of VC classes into maximum classes”. In: Measures of Complexity: Festschrift of Alexey Chervonenkis. Ed. by V. Vovk, H. Papadopoulos and A. Gammerman. Springer, 2015, pp. 303-325 [PDF; publisher link; BibTeX]

@article{fanaeepour2015the,
  title = {The {CASE} histogram: Privacy-aware processing of trajectory data using aggregates},
  author = {Maryam Fanaeepour and Lars Kulik and Egemen Tanin and Benjamin I. P. Rubinstein},
  journal = {GeoInformatica},
  volume = {19},
  number = {4},
  pages = {747--798},
  year = {2015},
  month = {Jul},
  publisher = {Springer},
}

• Fanaeepour, Maryam, Lars Kulik, Egemen Tanin, and Benjamin I. P. Rubinstein. “The CASE histogram: Privacy-aware processing of trajectory data using aggregates”. In: GeoInformatica 19.4 (Jul. 2015), pp. 747-798 [publisher link; BibTeX]

2014

@inproceedings{dimitrakakis2014robust,
  title = {Robust and private {B}ayesian inference},
  author = {Christos Dimitrakakis and Blaine Nelson and Aikaterini Mitrokotsa and Benjamin I. P. Rubinstein},
  booktitle = {25th International Conference on Algorithmic Learning Theory},
  series = {ALT},
  pages = {291--305},
  year = {2014},
  month = {Oct},
  organization = {Springer},
}

• Dimitrakakis, Christos, Blaine Nelson, Aikaterini Mitrokotsa, and Benjamin I. P. Rubinstein. “Robust and private Bayesian inference”. In: 25th International Conference on Algorithmic Learning Theory. ALT. Springer. Oct. 2014, pp. 291-305 [PDF; BibTeX]

@incollection{biggio2014security,
  title = {Security evaluation of support vector machines in adversarial environments},
  author = {Battista Biggio and Igino Corona and Blaine Nelson and Benjamin I. P. Rubinstein and Davide Maiorca and Giorgio Fumera and Giorgio Giacinto and Fabio Roli},
  editor = {Y. Ma and G. Guo},
  booktitle = {Support Vector Machines Applications},
  pages = {105--153},
  year = {2014},
  month = {Feb},
  publisher = {Springer},
}

• Biggio, Battista, Igino Corona, Blaine Nelson, Benjamin I. P. Rubinstein, Davide Maiorca, Giorgio Fumera, Giorgio Giacinto, and Fabio Roli. “Security evaluation of support vector machines in adversarial environments”. In: Support Vector Machines Applications. Ed. by Y. Ma and G. Guo. Springer, Feb. 2014, pp. 105-153 [full; publisher link; BibTeX]

@inproceedings{dimitrakakis2014proceedings,
  author = {Christos Dimitrakakis and Aikaterini Mitrokotsa and Benjamin I. P. Rubinstein},
  title = {Proceedings of the 7th Workshop on Artificial Intelligence and Security (AISec)},
  booktitle = {Proceedings of the 2014 ACM Conference on Computer and Communications Security},
  series = {CCS},
  pages = {1--124},
  publisher = {ACM Press},
  year = {2014},
}

• Dimitrakakis, Christos, Aikaterini Mitrokotsa, and Benjamin I. P. Rubinstein. “Proceedings of the 7th Workshop on Artificial Intelligence and Security (AISec)”. In: Proceedings of the 2014 ACM Conference on Computer and Communications Security. CCS. ACM Press, 2014, pp. 1-124 [publisher link; BibTeX]

2012

@article{zhao2012a,
  title = {A {B}ayesian approach to discovering truth from conflicting sources for data integration},
  author = {Bo Zhao and Benjamin I. P. Rubinstein and Jim Gemmell and Jiawei Han},
  journal = {Proceedings of the VLDB Endowment},
  volume = {5},
  number = {6},
  pages = {550--561},
  year = {2012},
  month = {Feb},
  publisher = {VLDB Endowment},
}

• Zhao, Bo, Benjamin I. P. Rubinstein, Jim Gemmell, and Jiawei Han. “A Bayesian approach to discovering truth from conflicting sources for data integration”. In: Proceedings of the VLDB Endowment 5.6 (Feb. 2012), pp. 550-561 [PDF; BibTeX]

@article{rubinstein2012on,
  title = {On the stability of empirical risk minimization in the presence of multiple risk minimizers},
  author = {Benjamin I. P. Rubinstein and Aleksandr Simma},
  journal = {IEEE Transactions on Information Theory},
  volume = {58},
  number = {7},
  pages = {4160--4163},
  year = {2012},
  month = {Jul},
  publisher = {IEEE},
}

• Rubinstein, Benjamin I. P. and Aleksandr Simma. “On the stability of empirical risk minimization in the presence of multiple risk minimizers”. In: IEEE Transactions on Information Theory 58.7 (Jul. 2012), pp. 4160-4163 [PDF; BibTeX]

@article{nelson2012query,
  title = {Query strategies for evading convex-inducing classifiers},
  author = {Blaine Nelson and Benjamin I. P. Rubinstein and Ling Huang and Anthony D. Joseph and Steven J. Lee and Satish Rao and J. D. Tygar},
  journal = {Journal of Machine Learning Research},
  volume = {13},
  number = {May},
  publisher = {MIT Press},
  pages = {1293--1332},
  year = {2012},
}

• Nelson, Blaine, Benjamin I. P. Rubinstein, Ling Huang, Anthony D. Joseph, Steven J. Lee, Satish Rao, and J. D. Tygar. “Query strategies for evading convex-inducing classifiers”. In: Journal of Machine Learning Research 13.May (2012), pp. 1293-1332 [PDF; BibTeX]

@article{rubinstein2012a,
  title = {A geometric approach to sample compression},
  author = {Benjamin I. P. Rubinstein and J. Hyam Rubinstein},
  journal = {Journal of Machine Learning Research},
  volume = {13},
  number = {Apr},
  publisher = {MIT Press},
  pages = {1221--1261},
  year = {2012},
}

• Rubinstein, Benjamin I. P. and J. Hyam Rubinstein. “A geometric approach to sample compression”. In: Journal of Machine Learning Research 13.Apr (2012), pp. 1221-1261 [PDF; BibTeX]

@article{rubinstein2012learning,
  title = {Learning in a large function space: Privacy-preserving mechanisms for {SVM} learning},
  author = {Benjamin I. P. Rubinstein and Peter L. Bartlett and Ling Huang and Nina Taft},
  journal = {Journal of Privacy and Confidentiality},
  volume = {4},
  number = {1},
  pages = {65--100},
  year = {2012},
  month = {Aug},
  note = {Special Issue on Statistical and Learning-Theoretic Challenges in Data Privacy},
}

• Rubinstein, Benjamin I. P., Peter L. Bartlett, Ling Huang, and Nina Taft. “Learning in a large function space: Privacy-preserving mechanisms for SVM learning”. In: Journal of Privacy and Confidentiality 4.1 (Aug. 2012). Special Issue on Statistical and Learning-Theoretic Challenges in Data Privacy, pp. 65-100 [PDF; full; BibTeX]

@article{barth2012a,
  title = {A learning-based approach to reactive security},
  author = {Adam Barth and Benjamin I. P. Rubinstein and Mukund Sundararajan and John C Mitchell and Dawn Song and Peter L. Bartlett},
  journal = {IEEE Transactions on Dependable and Secure Computing},
  volume = {9},
  number = {4},
  pages = {482--493},
  year = {2012},
  month = {Jul},
  publisher = {IEEE},
}

• Barth, Adam, Benjamin I. P. Rubinstein, Mukund Sundararajan, John C Mitchell, Dawn Song, and Peter L. Bartlett. “A learning-based approach to reactive security”. In: IEEE Transactions on Dependable and Secure Computing 9.4 (Jul. 2012), pp. 482-493 [publisher link; BibTeX]

@inproceedings{negahban2012scaling,
  title = {Scaling multiple-source entity resolution using statistically efficient transfer learning},
  author = {Sahand N. Negahban and Benjamin I. P. Rubinstein and Jim Gemmell},
  booktitle = {Proceedings of the 21st ACM International Conference on Information and Knowledge Management},
  series = {CIKM},
  pages = {2224--2228},
  year = {2012},
  month = {Oct},
  organization = {ACM},
}

• Negahban, Sahand N., Benjamin I. P. Rubinstein, and Jim Gemmell. “Scaling multiple-source entity resolution using statistically efficient transfer learning”. In: Proceedings of the 21st ACM International Conference on Information and Knowledge Management. CIKM. ACM. Oct. 2012, pp. 2224-2228 [full; publisher link; BibTeX]

@inproceedings{cardenas2012fifth,
  title = {Fifth ACM Workshop on Artificial Intelligence and Security (AISec)},
  author = {Alvaro A. Cardenas and Blaine Nelson and Benjamin I. P. Rubinstein},
  booktitle = {Proceedings of the 2012 ACM Conference on Computer and Communications Security},
  series = {CCS},
  pages = {1--110},
  year = {2012},
  month = {Oct},
  organization = {ACM},
}

• Cardenas, Alvaro A., Blaine Nelson, and Benjamin I. P. Rubinstein. “Fifth ACM Workshop on Artificial Intelligence and Security (AISec)”. In: Proceedings of the 2012 ACM Conference on Computer and Communications Security. CCS. ACM. Oct. 2012, pp. 1-110 [publisher link; BibTeX]

2011

@inproceedings{huang2011adversarial,
  title = {Adversarial machine learning},
  author = {Ling Huang and Anthony D. Joseph and Blaine Nelson and Benjamin I. P. Rubinstein and J. D. Tygar},
  booktitle = {Proceedings of the 4th ACM Workshop on Security and Artificial Intelligence},
  pages = {43--58},
  year = {2011},
  month = {Oct},
  organization = {ACM},
}

• Huang, Ling, Anthony D. Joseph, Blaine Nelson, Benjamin I. P. Rubinstein, and J. D. Tygar. “Adversarial machine learning”. In: Proceedings of the 4th ACM Workshop on Security and Artificial Intelligence. ACM. Oct. 2011, pp. 43-58 [PDF; BibTeX]

@inproceedings{narayanan2011link,
  title = {Link prediction by de-anonymization: How we won the {K}aggle social network challenge},
  author = {Arvind Narayanan and Elaine Shi and Benjamin I. P. Rubinstein},
  booktitle = {The 2011 International Joint Conference on Neural Networks},
  series = {IJCNN},
  pages = {1825--1834},
  year = {2011},
  month = {Feb},
  organization = {IEEE},
}

• Narayanan, Arvind, Elaine Shi, and Benjamin I. P. Rubinstein. “Link prediction by de-anonymization: How we won the Kaggle social network challenge”. In: The 2011 International Joint Conference on Neural Networks. IJCNN. IEEE. Feb. 2011, pp. 1825-1834 [PDF; BibTeX]

@techreport{barth2011how,
  title = {How Open Should Open Source Be?},
  author = {Adam Barth and Saung Li and Benjamin I. P. Rubinstein and Dawn Song},
  institution = {Department of Electrical Engineering \& Computer Sciences, UC Berkeley},
  type = {technical report},
  number = {UCB/EECS-2011-98},
  year = {2011},
  month = {Aug},
}

• Barth, Adam, Saung Li, Benjamin I. P. Rubinstein, and Dawn Song. How Open Should Open Source Be? technical report UCB/EECS-2011-98. Department of Electrical Engineering & Computer Sciences, UC Berkeley, Aug. 2011 [PDF; BibTeX]

@techreport{gemmell2011improving,
  title = {Improving entity resolution with global constraints},
  author = {Jim Gemmell and Benjamin I. P. Rubinstein and Ashok K. Chandra},
  institution = {Microsoft Research},
  type = {technical report},
  number = {MSR-TR-2011-100},
  year = {2011},
  month = {Aug},
}

• Gemmell, Jim, Benjamin I. P. Rubinstein, and Ashok K. Chandra. Improving entity resolution with global constraints. technical report MSR-TR-2011-100. Microsoft Research, Aug. 2011 [PDF; BibTeX]

@inproceedings{cardenas2011proceedings,
  author = {Alvaro A. Cardenas and Rachel Greenstadt and Benjamin I. P. Rubinstein},
  title = {Proceedings of the 4th Workshop on Artificial Intelligence and Security (AISec)},
  booktitle = {Proceedings of the 2011 ACM Conference on Computer and Communications Security},
  series = {CCS},
  pages = {1--116},
  publisher = {ACM Press},
  year = {2011},
  month = {Oct},
}

• Cardenas, Alvaro A., Rachel Greenstadt, and Benjamin I. P. Rubinstein. “Proceedings of the 4th Workshop on Artificial Intelligence and Security (AISec)”. In: Proceedings of the 2011 ACM Conference on Computer and Communications Security. CCS. ACM Press, Oct. 2011, pp. 1-116 [publisher link; BibTeX]

2010

@inproceedings{nelson2010nearoptimal,
  title = {Near-Optimal Evasion of Convex-Inducing Classifiers.},
  author = {Blaine Nelson and Benjamin I. P. Rubinstein and Ling Huang and Anthony D. Joseph and Shing-hon Lau and Steven J. Lee and Satish Rao and Anthony Tran and J. Doug Tygar},
  booktitle = {Proceedings of the Thirteenth International Conference on Artificial Intelligence and Statistics},
  series = {AISTATS},
  pages = {549--556},
  year = {2010},
}

• Nelson, Blaine, Benjamin I. P. Rubinstein, Ling Huang, Anthony D. Joseph, Shing-hon Lau, Steven J. Lee, Satish Rao, Anthony Tran, and J. Doug Tygar. “Near-Optimal Evasion of Convex-Inducing Classifiers.” In: Proceedings of the Thirteenth International Conference on Artificial Intelligence and Statistics. AISTATS. 2010, pp. 549-556 [PDF; BibTeX]

@inproceedings{barth2010a,
  title = {A learning-based approach to reactive security},
  author = {Adam Barth and Benjamin I. P. Rubinstein and Mukund Sundararajan and John C. Mitchell and Dawn Song and Peter L. Bartlett},
  booktitle = {Proceedings of the Fourteenth International Conference on Financial Cryptography and Data Security},
  series = {FC},
  pages = {192--206},
  year = {2010},
}

• Barth, Adam, Benjamin I. P. Rubinstein, Mukund Sundararajan, John C. Mitchell, Dawn Song, and Peter L. Bartlett. “A learning-based approach to reactive security”. In: Proceedings of the Fourteenth International Conference on Financial Cryptography and Data Security. FC. 2010, pp. 192-206 [PDF; BibTeX]

@inproceedings{nelson2010classifier,
  title = {Classifier evasion: Models and open problems},
  author = {Blaine Nelson and Benjamin I. P. Rubinstein and Ling Huang and Anthony D. Joseph and J. D. Tygar},
  booktitle = {International Workshop on Privacy and Security Issues in Data Mining and Machine Learning},
  series = {PSDML},
  pages = {92--98},
  year = {2010},
}

• Nelson, Blaine, Benjamin I. P. Rubinstein, Ling Huang, Anthony D. Joseph, and J. D. Tygar. “Classifier evasion: Models and open problems”. In: International Workshop on Privacy and Security Issues in Data Mining and Machine Learning. PSDML. 2010, pp. 92-98 [PDF; BibTeX]

@phdthesis{rubinstein2010secure,
  title = {Secure Learning and Learning for Security: Research in the Intersection},
  author = {Benjamin I. P. Rubinstein},
  year = {2010},
  month = {May},
  school = {Department of Electrical Engineering \& Computer Sciences, University of California, Berkeley},
  type = {PhD dissertation},
}

• Rubinstein, Benjamin I. P. “Secure Learning and Learning for Security: Research in the Intersection”. PhD dissertation. Department of Electrical Engineering & Computer Sciences, University of California, Berkeley, May. 2010 [PDF; BibTeX]

2009

@inproceedings{ghosh2009adaptive,
  title = {Adaptive bidding for display advertising},
  author = {Arpita Ghosh and Benjamin I. P. Rubinstein and Sergei Vassilvitskii and Martin Zinkevich},
  booktitle = {Proceedings of the 18th International Conference on World Wide Web},
  series = {WWW},
  pages = {251--260},
  year = {2009},
  organization = {ACM},
}

• Ghosh, Arpita, Benjamin I. P. Rubinstein, Sergei Vassilvitskii, and Martin Zinkevich. “Adaptive bidding for display advertising”. In: Proceedings of the 18th International Conference on World Wide Web. WWW. ACM. 2009, pp. 251-260 [PDF; BibTeX]

@article{rubinstein2009shifting,
  title = {Shifting: One-inclusion mistake bounds and sample compression},
  author = {Benjamin I. P. Rubinstein and Peter L. Bartlett and J. Hyam Rubinstein},
  journal = {Journal of Computer and System Sciences},
  volume = {75},
  number = {1},
  pages = {37--59},
  year = {2009},
}

• Rubinstein, Benjamin I. P., Peter L. Bartlett, and J. Hyam Rubinstein. “Shifting: One-inclusion mistake bounds and sample compression”. In: Journal of Computer and System Sciences 75.1 (2009), pp. 37-59 [PDF; corrigendum; BibTeX]

@inproceedings{rubinstein2009antidote,
  title = {{ANTIDOTE}: Understanding and defending against poisoning of anomaly detectors},
  author = {Benjamin I. P. Rubinstein and Blaine Nelson and Ling Huang and Anthony D. Joseph and Shing-hon Lau and Satish Rao and Nina Taft and J. D. Tygar},
  booktitle = {Proceedings of the 9th ACM SIGCOMM Internet Measurement Conference},
  series = {IMC},
  pages = {1--14},
  year = {2009},
  organization = {ACM},
}

• Rubinstein, Benjamin I. P., Blaine Nelson, Ling Huang, Anthony D. Joseph, Shing-hon Lau, Satish Rao, Nina Taft, and J. D. Tygar. “ANTIDOTE: Understanding and defending against poisoning of anomaly detectors”. In: Proceedings of the 9th ACM SIGCOMM Internet Measurement Conference. IMC. ACM. 2009, pp. 1-14 [PDF; BibTeX]

@article{rubinstein2009stealthy,
  title = {Stealthy poisoning attacks on {PCA}-based anomaly detectors},
  author = {Benjamin I. P. Rubinstein and Blaine Nelson and Ling Huang and Anthony D. Joseph and Shing-hon Lau and Satish Rao and Nina Taft and J. D. Tygar},
  journal = {ACM SIGMETRICS Performance Evaluation Review},
  volume = {37},
  number = {2},
  pages = {73--74},
  year = {2009},
  publisher = {ACM},
}

• Rubinstein, Benjamin I. P., Blaine Nelson, Ling Huang, Anthony D. Joseph, Shing-hon Lau, Satish Rao, Nina Taft, and J. D. Tygar. “Stealthy poisoning attacks on PCA-based anomaly detectors”. In: ACM SIGMETRICS Performance Evaluation Review 37.2 (2009), pp. 73-74 [PDF; BibTeX]

@incollection{nelson2009misleading,
  title = {Misleading learners: Co-opting your spam filter},
  author = {Blaine Nelson and Marco Barreno and Fuching Jack Chi and Anthony D. Joseph and Benjamin I. P. Rubinstein and Udam Saini and Charles Sutton and J. D. Tygar and Kai Xia},
  booktitle = {Machine Learning in Cyber Trust: Security, Privacy, and Reliability},
  pages = {17--51},
  year = {2009},
  publisher = {Springer},
}

• Nelson, Blaine, Marco Barreno, Fuching Jack Chi, Anthony D. Joseph, Benjamin I. P. Rubinstein, Udam Saini, Charles Sutton, J. D. Tygar, and Kai Xia. “Misleading learners: Co-opting your spam filter”. In: Machine Learning in Cyber Trust: Security, Privacy, and Reliability. Springer, 2009, pp. 17-51 [publisher link; BibTeX]

@mastersthesis{rubinstein2009bshifting,
  author = {Benjamin I. P. Rubinstein},
  title = {Shifting in the n-Cube: Online Mistake Bounds and the Sample Compression Conjecture},
  school = {Faculty of Engineering, University of Melbourne},
  year = {2009},
  type = {MCompSci thesis},
}

• Rubinstein, Benjamin I. P. “Shifting in the n-Cube: Online Mistake Bounds and the Sample Compression Conjecture”. MCompSci thesis. Faculty of Engineering, University of Melbourne, 2009 [full; BibTeX]

2008

@inproceedings{rubinstein2008geometric,
  title = {Geometric \& Topological Representations of Maximum Classes with Applications to Sample Compression},
  author = {J. Hyam Rubinstein and Benjamin I. P. Rubinstein},
  booktitle = {Proceedings of the 21st Annual Conference on Learning Theory},
  series = {COLT},
  pages = {299--310},
  year = {2008},
}

• Rubinstein, J. Hyam and Benjamin I. P. Rubinstein. “Geometric & Topological Representations of Maximum Classes with Applications to Sample Compression”. In: Proceedings of the 21st Annual Conference on Learning Theory. COLT. 2008, pp. 299-310 [PDF; BibTeX]

@inproceedings{rubinstein2008evading,
  title = {Evading anomaly detection through variance injection attacks on {PCA}},
  author = {Benjamin I. P. Rubinstein and Blaine Nelson and Ling Huang and Anthony D. Joseph and Shing-hon Lau and Nina Taft and J. Doug Tygar},
  booktitle = {Proceedings of the 11th International Symposium on Recent Advances in Intrusion Detection},
  series = {RAID},
  pages = {394--395},
  year = {2008},
}

• Rubinstein, Benjamin I. P., Blaine Nelson, Ling Huang, Anthony D. Joseph, Shing-hon Lau, Nina Taft, and J. Doug Tygar. “Evading anomaly detection through variance injection attacks on PCA”. In: Proceedings of the 11th International Symposium on Recent Advances in Intrusion Detection. RAID. 2008, pp. 394-395 [PDF; Winner of RAID08 best poster award; BibTeX]

@inproceedings{nelson2008exploiting,
  title = {Exploiting Machine Learning to Subvert Your Spam Filter.},
  author = {Blaine Nelson and Marco Barreno and Fuching Jack Chi and Anthony D. Joseph and Benjamin I. P. Rubinstein and Udam Saini and Charles A. Sutton and J. Doug Tygar and Kai Xia},
  booktitle = {First USENIX Workshop on Large-scale Exploits and Emergent Threats},
  series = {LEET},
  pages = {1--9},
  year = {2008},
}

• Nelson, Blaine, Marco Barreno, Fuching Jack Chi, Anthony D. Joseph, Benjamin I. P. Rubinstein, Udam Saini, Charles A. Sutton, J. Doug Tygar, and Kai Xia. “Exploiting Machine Learning to Subvert Your Spam Filter.” In: First USENIX Workshop on Large-scale Exploits and Emergent Threats. LEET. 2008, pp. 1-9 [PDF; BibTeX]

@inproceedings{barreno2008open,
  title = {Open problems in the security of learning},
  author = {Marco Barreno and Peter L. Bartlett and Fuching Jack Chi and Anthony D. Joseph and Blaine Nelson and Benjamin I. P. Rubinstein and Udam Saini and J. Doug Tygar},
  booktitle = {Proceedings of the 1st ACM Workshop on Artificial Intelligence \& Security},
  series = {AISec},
  pages = {19--26},
  year = {2008},
  organization = {ACM},
}

• Barreno, Marco, Peter L. Bartlett, Fuching Jack Chi, Anthony D. Joseph, Blaine Nelson, Benjamin I. P. Rubinstein, Udam Saini, and J. Doug Tygar. “Open problems in the security of learning”. In: Proceedings of the 1st ACM Workshop on Artificial Intelligence & Security. AISec. ACM. 2008, pp. 19-26 [PDF; BibTeX]

@techreport{rubinstein2008compromising,
  title = {Compromising {PCA}-based anomaly detectors for network-wide traffic},
  author = {Benjamin I. P. Rubinstein and Blaine Nelson and Ling Huang and Anthony D. Joseph and Shing-hon Lau and Nina Taft and Doug Tygar},
  institution = {EECS Department, University of California, Berkeley},
  type = {technical report},
  number = {UCB/EECS-2008-73},
  year = {2008},
}

• Rubinstein, Benjamin I. P., Blaine Nelson, Ling Huang, Anthony D. Joseph, Shing-hon Lau, Nina Taft, and Doug Tygar. Compromising PCA-based anomaly detectors for network-wide traffic. technical report UCB/EECS-2008-73. EECS Department, University of California, Berkeley, 2008 [PDF; BibTeX]

2007

@inproceedings{rubinstein2007shifting,
  title = {Shifting, one-inclusion mistake bounds and tight multiclass expected risk bounds},
  author = {Benjamin I. P. Rubinstein and Peter L. Bartlett and J. Hyam Rubinstein},
  booktitle = {Advances in Neural Information Processing Systems 19},
  series = {NIPS},
  pages = {1193--1200},
  year = {2007},
}

• Rubinstein, Benjamin I. P., Peter L. Bartlett, and J. Hyam Rubinstein. “Shifting, one-inclusion mistake bounds and tight multiclass expected risk bounds”. In: Advances in Neural Information Processing Systems 19. NIPS. 2007, pp. 1193-1200 [PDF; BibTeX]

Pre 2007

@proceedings{abraham2004proceedings,
  author = {Gad Abraham and Benjamin I. P. Rubinstein},
  title = {Proceedings of the Second Australian Students' Computing Conference},
  series = {AUSCC},
  note = { 175 pages},
  year = {2004},
}

• Proceedings of the Second Australian Students’ Computing Conference. AUSCC. 175 pages. 2004. ISBN: 0-975-71730-8 [PDF; BibTeX]

@proceedings{rubinstein2003proceedings,
  author = {Benjamin I. P. Rubinstein and Nelson Chan and K. K. Kshetrapalapuram},
  title = {Proceedings of the First Australian Undergraduate Students' Computer Conference},
  series = {AUSCC},
  note = {126 pages},
  year = {2003},
}

• Proceedings of the First Australian Undergraduate Students’ Computer Conference. AUSCC. 126 pages. 2003. ISBN: 0-646-42751-2 [PDF; BibTeX]

@article{rubinstein2003machine,
  title = {Machine learning in low-level microarray analysis},
  author = {Benjamin I. P. Rubinstein and Jon McAuliffe and Simon Cawley and Marimuthu Palaniswami and Kotagiri Ramamohanarao and Terence P. Speed},
  journal = {ACM SIGKDD Explorations Newsletter},
  volume = {5},
  number = {2},
  pages = {130--139},
  year = {2003},
  publisher = {ACM},
  note = {Special Issue on Microarray Data Mining},
}

• Rubinstein, Benjamin I. P., Jon McAuliffe, Simon Cawley, Marimuthu Palaniswami, Kotagiri Ramamohanarao, and Terence P. Speed. “Machine learning in low-level microarray analysis”. In: ACM SIGKDD Explorations Newsletter 5.2 (2003). Special Issue on Microarray Data Mining, pp. 130-139 [PDF; BibTeX]

@inproceedings{rubinstein2001evolving,
  title = {Evolving quantum circuits using genetic programming},
  author = {Benjamin I. P. Rubinstein},
  booktitle = {Proceedings of the 2001 Congress on Evolutionary Computation},
  series = {CEC},
  pages = {144--151},
  year = {2001},
  organization = {IEEE},
}

• Rubinstein, Benjamin I. P. “Evolving quantum circuits using genetic programming”. In: Proceedings of the 2001 Congress on Evolutionary Computation. CEC. IEEE. 2001, pp. 144-151 [PDF; Winner of IEEE Computer Society’s Lance Stafford Larson Scholarship for best undergraduate student paper worldwide; BibTeX]