Benjamin I. P. Rubinstein

199 papers A* 39A 7B 9Misc 2Journal 109Unranked 30

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Semantic-aware Adversarial Fine-tuning for CLIP. CoRR Jiacheng Zhang, Jinhao Li, Hanxun Huang, Sarah M. Erfani, Benjamin I. P. Rubinstein, Feng Liu
2026	J	`jnl`	Semantic-aware Adversarial Fine-tuning for CLIP. Trans. Mach. Learn. Res. Jiacheng Zhang, Jinhao Li, Hanxun Huang, Sarah Monazam Erfani, Benjamin I. P. Rubinstein, Feng Liu
2025	J	`jnl`	AdaptDel: Adaptable Deletion Rate Randomized Smoothing for Certified Robustness. CoRR Zhuoqun Huang, Neil G. Marchant, Olga Ohrimenko, Benjamin I. P. Rubinstein
2025	J	`jnl`	DDAD: A Two-pronged Adversarial Defense Based on Distributional Discrepancy. CoRR Jiacheng Zhang, Benjamin I. P. Rubinstein, Jingfeng Zhang, Feng Liu
2025	J	`jnl`	DynamiQ: Unlocking the Potential of Dynamic Task Allocation in Parallel Fuzzing. CoRR Wenqi Yan, Toby Murray, Benjamin I. P. Rubinstein, Van-Thuan Pham
2025	J	`jnl`	Fox in the Henhouse: Supply-Chain Backdoor Attacks Against Reinforcement Learning. CoRR Shijie Liu, Andrew C. Cullen, Paul Montague, Sarah M. Erfani, Benjamin I. P. Rubinstein
2025	A*	`conf`	Multi-level Certified Defense Against Poisoning Attacks in Offline Reinforcement Learning. ICLR Shijie Liu, Andrew Craig Cullen, Paul Montague, Sarah Monazam Erfani, Benjamin I. P. Rubinstein
2025	J	`jnl`	Multi-level Certified Defense Against Poisoning Attacks in Offline Reinforcement Learning. CoRR Shijie Liu, Andrew C. Cullen, Paul Montague, Sarah M. Erfani, Benjamin I. P. Rubinstein
2025	A*	`conf`	One Stone, Two Birds: Enhancing Adversarial Defense Through the Lens of Distributional Discrepancy. ICML Jiacheng Zhang, Benjamin I. P. Rubinstein, Jingfeng Zhang, Feng Liu
2025	—	`conf`	Position: Certified Robustness Does Not (Yet) Imply Model Security. ICML (Position Papers) Andrew Craig Cullen, Paul Montague, Sarah Monazam Erfani, Benjamin I. P. Rubinstein
2025	J	`jnl`	Position: Certified Robustness Does Not (Yet) Imply Model Security. CoRR Andrew C. Cullen, Paul Montague, Sarah M. Erfani, Benjamin I. P. Rubinstein
2025	J	`jnl`	RS-Reg: Probabilistic and Robust Certified Regression through Randomized Smoothing. Trans. Mach. Learn. Res. Aref Miri Rekavandi, Olga Ohrimenko, Benjamin I. P. Rubinstein
2025	—	`conf`	TUBA: Cross-Lingual Transferability of Backdoor Attacks in LLMs with Instruction Tuning. ACL (Findings) Xuanli He, Jun Wang, Qiongkai Xu, Pasquale Minervini, Pontus Stenetorp, Benjamin I. P. Rubinstein, Trevor Cohn
2025	J	`jnl`	Where is the Watermark? Interpretable Watermark Detection at the Block Level. CoRR Maria Bulychev, Neil G. Marchant, Benjamin I. P. Rubinstein
2024	J	`jnl`	Adaptive Data Analysis for Growing Data. CoRR Neil G. Marchant, Benjamin I. P. Rubinstein
2024	J	`jnl`	Backdoor Attack on Multilingual Machine Translation. CoRR Jun Wang, Qiongkai Xu, Xuanli He, Benjamin I. P. Rubinstein, Trevor Cohn
2024	—	`conf`	Backdoor Attacks on Multilingual Machine Translation. NAACL-HLT Jun Wang, Qiongkai Xu, Xuanli He, Benjamin I. P. Rubinstein, Trevor Cohn
2024	—	`conf`	CERT-ED: Certifiably Robust Text Classification for Edit Distance. EMNLP (Findings) Zhuoqun Huang, Neil G. Marchant, Olga Ohrimenko, Benjamin I. P. Rubinstein
2024	J	`jnl`	CERT-ED: Certifiably Robust Text Classification for Edit Distance. CoRR Zhuoqun Huang, Neil G. Marchant, Olga Ohrimenko, Benjamin I. P. Rubinstein
2024	A*	`conf`	Certified Adversarial Robustness via Randomized α-Smoothing for Regression Models. NeurIPS Aref Miri Rekavandi, Farhad Farokhi, Olga Ohrimenko, Benjamin I. P. Rubinstein
2024	—	`conf`	Designing an Adaptive AI System for Operation on Board the SpIRIT Nano-Satellite. AI (1) Zaher Joukhadar, Jonathan Morgan, Christopher Bayliss, Miguel Ortiz del Castillo, Jack McRobbie, Robert Mearns, Krista A. Ehinger, Benjamin I. P. Rubinstein, Richard O. Sinnott, Michele Trenti, James Bailey
2024	A*	`conf`	Elephants Do Not Forget: Differential Privacy with State Continuity for Privacy Budget. CCS Jiankai Jin, Chitchanok Chuengsatiansup, Toby Murray, Benjamin I. P. Rubinstein, Yuval Yarom, Olga Ohrimenko
2024	J	`jnl`	Elephants Do Not Forget: Differential Privacy with State Continuity for Privacy Budget. CoRR Jiankai Jin, Chitchanok Chuengsatiansup, Toby Murray, Benjamin I. P. Rubinstein, Yuval Yarom, Olga Ohrimenko
2024	A*	`conf`	Et Tu Certifications: Robustness Certificates Yield Better Adversarial Examples. ICML Andrew C. Cullen, Shijie Liu, Paul Montague, Sarah Monazam Erfani, Benjamin I. P. Rubinstein
2024	—	`conf`	Getting a-Round Guarantees: Floating-Point Attacks on Certified Robustness. AISec@CCS Jiankai Jin, Olga Ohrimenko, Benjamin I. P. Rubinstein
2024	A*	`conf`	It's Simplex! Disaggregating Measures to Improve Certified Robustness. SP Andrew C. Cullen, Paul Montague, Shijie Liu, Sarah M. Erfani, Benjamin I. P. Rubinstein
2024	—	`conf`	Mitigating Challenges of the Space Environment for Onboard Artificial Intelligence: Design Overview of the Imaging Payload on SpIRIT. CVPR Workshops Miguel Ortiz del Castillo, Jonathan Morgan, Jack McRobbie, Clint Therakam, Zaher Joukhadar, Robert Mearns, Simon Barraclough, Richard O. Sinnott, Andrew Woods, Chris Bayliss, Kris Ehinger, Benjamin I. P. Rubinstein, James Bailey, Airlie Chapman, Michele Trenti
2024	J	`jnl`	Mitigating Challenges of the Space Environment for Onboard Artificial Intelligence: Design Overview of the Imaging Payload on SpIRIT. CoRR Miguel Ortiz del Castillo, Jonathan Morgan, Jack McRobbie, Clint Therakam, Zaher Joukhadar, Robert Mearns, Simon Barraclough, Richard O. Sinnott, Andrew Woods, Chris Bayliss, Kris Ehinger, Benjamin I. P. Rubinstein, James Bailey, Airlie Chapman, Michele Trenti
2024	J	`jnl`	RS-Reg: Probabilistic and Robust Certified Regression Through Randomized Smoothing. CoRR Aref Miri Rekavandi, Olga Ohrimenko, Benjamin I. P. Rubinstein
2024	J	`jnl`	SEEP: Training Dynamics Grounds Latent Representation Search for Mitigating Backdoor Poisoning Attacks. CoRR Xuanli He, Qiongkai Xu, Jun Wang, Benjamin I. P. Rubinstein, Trevor Cohn
2024	J	`jnl`	SEEP: Training Dynamics Grounds Latent Representation Search for Mitigating Backdoor Poisoning Attacks. Trans. Assoc. Comput. Linguistics Xuanli He, Qiongkai Xu, Jun Wang, Benjamin I. P. Rubinstein, Trevor Cohn
2024	J	`jnl`	To Act or Not to Act: An Adversarial Game for Securing Vehicle Platoons. IEEE Trans. Inf. Forensics Secur. Guoxin Sun, Tansu Alpcan, Benjamin I. P. Rubinstein, Seyit Camtepe
2024	J	`jnl`	Transferring Troubles: Cross-Lingual Transferability of Backdoor Attacks in LLMs with Instruction Tuning. CoRR Xuanli He, Jun Wang, Qiongkai Xu, Pasquale Minervini, Pontus Stenetorp, Benjamin I. P. Rubinstein, Trevor Cohn
2024	A*	`conf`	Warm-Starting Contextual Bandits Under Latent Reward Scaling. ICDM Bastian Oetomo, R. Malinga Perera, Renata Borovica-Gajic, Benjamin I. P. Rubinstein
2023	A	`conf`	An Adversarial Strategic Game for Machine Learning as a Service using System Features. AAMAS Guoxin Sun, Tansu Alpcan, Seyit Camtepe, Andrew C. Cullen, Benjamin I. P. Rubinstein
2023	J	`jnl`	Bayesian Graphical Entity Resolution Using Exchangeable Random Partition Priors. CoRR Neil G. Marchant, Benjamin I. P. Rubinstein, Rebecca C. Steorts
2023	—	`conf`	Beyond the Coverage Plateau: A Comprehensive Study of Fuzz Blockers (Registered Report). FUZZING Wentao Gao, Van-Thuan Pham, Dongge Liu, Oliver Chang, Toby Murray, Benjamin I. P. Rubinstein
2023	J	`jnl`	Certified Robustness of Learning-based Static Malware Detectors. CoRR Zhuoqun Huang, Neil G. Marchant, Keane Lucas, Lujo Bauer, Olga Ohrimenko, Benjamin I. P. Rubinstein
2023	J	`jnl`	Cutting to the chase with warm-start contextual bandits. Knowl. Inf. Syst. Bastian Oetomo, R. Malinga Perera, Renata Borovica-Gajic, Benjamin I. P. Rubinstein
2023	—	`conf`	Efficient Index Learning via Model Reuse and Fine-tuning. ICDEW Guanli Liu, Jianzhong Qi, Lars Kulik, Kazuya Soga, Renata Borovica-Gajic, Benjamin I. P. Rubinstein
2023	A*	`conf`	Enhancing the Antidote: Improved Pointwise Certifications against Poisoning Attacks. AAAI Shijie Liu, Andrew C. Cullen, Paul Montague, Sarah M. Erfani, Benjamin I. P. Rubinstein
2023	J	`jnl`	Enhancing the Antidote: Improved Pointwise Certifications against Poisoning Attacks. CoRR Shijie Liu, Andrew C. Cullen, Paul Montague, Sarah M. Erfani, Benjamin I. P. Rubinstein
2023	J	`jnl`	Exploiting Certified Defences to Attack Randomised Smoothing. CoRR Andrew C. Cullen, Paul Montague, Shijie Liu, Sarah M. Erfani, Benjamin I. P. Rubinstein
2023	J	`jnl`	IMBERT: Making BERT Immune to Insertion-based Backdoor Attacks. CoRR Xuanli He, Jun Wang, Benjamin I. P. Rubinstein, Trevor Cohn
2023	J	`jnl`	It's Simplex! Disaggregating Measures to Improve Certified Robustness. CoRR Andrew C. Cullen, Paul Montague, Shijie Liu, Sarah M. Erfani, Benjamin I. P. Rubinstein
2023	A*	`conf`	Mitigating Backdoor Poisoning Attacks through the Lens of Spurious Correlation. EMNLP Xuanli He, Qiongkai Xu, Jun Wang, Benjamin I. P. Rubinstein, Trevor Cohn
2023	J	`jnl`	Mitigating Backdoor Poisoning Attacks through the Lens of Spurious Correlation. CoRR Xuanli He, Qiongkai Xu, Jun Wang, Benjamin I. P. Rubinstein, Trevor Cohn
2023	J	`jnl`	No DBA? No Regret! Multi-Armed Bandits for Index Tuning of Analytical and HTAP Workloads With Provable Guarantees. IEEE Trans. Knowl. Data Eng. R. Malinga Perera, Bastian Oetomo, Benjamin I. P. Rubinstein, Renata Borovica-Gajic
2023	J	`jnl`	Predicting dynamic spectrum allocation: a review covering simulation, modelling, and prediction. Artif. Intell. Rev. Andrew C. Cullen, Benjamin I. P. Rubinstein, Sithamparanathan Kandeepan, Barry Flower, Philip H. W. Leong
2023	A*	`conf`	RS-Del: Edit Distance Robustness Certificates for Sequence Classifiers via Randomized Deletion. NeurIPS Zhuoqun Huang, Neil G. Marchant, Keane Lucas, Lujo Bauer, Olga Ohrimenko, Benjamin I. P. Rubinstein
2022	J	`jnl`	A Graph Symmetrization Bound on Channel Information Leakage Under Blowfish Privacy. IEEE Trans. Inf. Theory Tobias Edwards, Benjamin I. P. Rubinstein, Zuhe Zhang, Sanming Zhou
2022	A*	`conf`	Are We There Yet? Timing and Floating-Point Attacks on Differential Privacy Systems. SP Jiankai Jin, Eleanor McMurtry, Benjamin I. P. Rubinstein, Olga Ohrimenko
2022	A*	`conf`	Double Bubble, Toil and Trouble: Enhancing Certified Robustness through Transitivity. NeurIPS Andrew C. Cullen, Paul Montague, Shijie Liu, Sarah M. Erfani, Benjamin I. P. Rubinstein
2022	J	`jnl`	Double Bubble, Toil and Trouble: Enhancing Certified Robustness through Transitivity. CoRR Andrew C. Cullen, Paul Montague, Shijie Liu, Sarah M. Erfani, Benjamin I. P. Rubinstein
2022	—	`conf`	Foiling Training-Time Attacks on Neural Machine Translation Systems. EMNLP (Findings) Jun Wang, Xuanli He, Benjamin I. P. Rubinstein, Trevor Cohn
2022	J	`jnl`	Getting a-Round Guarantees: Floating-Point Attacks on Certified Robustness. CoRR Jiankai Jin, Olga Ohrimenko, Benjamin I. P. Rubinstein
2022	J	`jnl`	HMAB: Self-Driving Hierarchy of Bandits for Integrated Physical Database Design Tuning. Proc. VLDB Endow. R. Malinga Perera, Bastian Oetomo, Benjamin I. P. Rubinstein, Renata Borovica-Gajic
2022	A*	`conf`	Hard to Forget: Poisoning Attacks on Certified Machine Unlearning. AAAI Neil G. Marchant, Benjamin I. P. Rubinstein, Scott Alfeld
2022	—	`conf`	Local Intrinsic Dimensionality Signals Adversarial Perturbations. CDC Sandamal Weerasinghe, Tamas Abraham, Tansu Alpcan, Sarah M. Erfani, Christopher Leckie, Benjamin I. P. Rubinstein
2022	—	`conf`	Measuring and Mitigating Name Biases in Neural Machine Translation. ACL (1) Jun Wang, Benjamin I. P. Rubinstein, Trevor Cohn
2022	—	`conf`	Securing Cyber-Physical Systems: Physics-Enhanced Adversarial Learning for Autonomous Platoons. ECML/PKDD (3) Guoxin Sun, Tansu Alpcan, Benjamin I. P. Rubinstein, Seyit Camtepe
2022	A	`conf`	State Selection Algorithms and Their Impact on The Performance of Stateful Network Protocol Fuzzing. SANER Dongge Liu, Van-Thuan Pham, Gidon Ernst, Toby Murray, Benjamin I. P. Rubinstein
2022	J	`jnl`	Testing the Robustness of Learned Index Structures. CoRR Matthias Bachfischer, Renata Borovica-Gajic, Benjamin I. P. Rubinstein
2022	A*	`conf`	Unlabelled Sample Compression Schemes for Intersection-Closed Classes and Extremal Classes. NeurIPS Joachim Hyam Rubinstein, Benjamin I. P. Rubinstein
2022	J	`jnl`	Unlabelled Sample Compression Schemes for Intersection-Closed Classes and Extremal Classes. CoRR J. Hyam Rubinstein, Benjamin I. P. Rubinstein
2021	—	`conf`	A Communication Security Game on Switched Systems for Autonomous Vehicle Platoons. CDC Guoxin Sun, Tansu Alpcan, Benjamin I. P. Rubinstein, Seyit Camtepe
2021	J	`jnl`	A Communication Security Game on Switched Systems for Autonomous Vehicle Platoons. CoRR Guoxin Sun, Tansu Alpcan, Benjamin I. P. Rubinstein, Seyit Camtepe
2021	A*	`conf`	A Targeted Attack on Black-Box Neural Machine Translation with Parallel Data Poisoning. WWW Chang Xu, Jun Wang, Yuqing Tang, Francisco Guzmán, Benjamin I. P. Rubinstein, Trevor Cohn
2021	J	`jnl`	Are We There Yet? Timing and Floating-Point Attacks on Differential Privacy Systems. CoRR Jiankai Jin, Eleanor McMurtry, Benjamin I. P. Rubinstein, Olga Ohrimenko
2021	—	`conf`	As Easy as 1, 2, 3: Behavioural Testing of NMT Systems for Numerical Translation. ACL/IJCNLP (Findings) Jun Wang, Chang Xu, Francisco Guzmán, Ahmed El-Kishky, Benjamin I. P. Rubinstein, Trevor Cohn
2021	J	`jnl`	As Easy as 1, 2, 3: Behavioural Testing of NMT Systems for Numerical Translation. CoRR Jun Wang, Chang Xu, Francisco Guzmán, Ahmed El-Kishky, Benjamin I. P. Rubinstein, Trevor Cohn
2021	A*	`conf`	Closing the BIG-LID: An Effective Local Intrinsic Dimensionality Defense for Nonlinear Regression Poisoning. IJCAI Sandamal Weerasinghe, Tamas Abraham, Tansu Alpcan, Sarah M. Erfani, Christopher Leckie, Benjamin I. P. Rubinstein
2021	A*	`conf`	Cutting to the Chase with Warm-Start Contextual Bandits. ICDM Bastian Oetomo, R. Malinga Perera, Renata Borovica-Gajic, Benjamin I. P. Rubinstein
2021	A*	`conf`	DBA bandits: Self-driving index tuning under ad-hoc, analytical workloads with safety guarantees. ICDE R. Malinga Perera, Bastian Oetomo, Benjamin I. P. Rubinstein, Renata Borovica-Gajic
2021	J	`jnl`	Hard to Forget: Poisoning Attacks on Certified Machine Unlearning. CoRR Neil G. Marchant, Benjamin I. P. Rubinstein, Scott Alfeld
2021	A*	`conf`	Invertible Concept-based Explanations for CNN Models with Non-negative Concept Activation Vectors. AAAI Ruihan Zhang, Prashan Madumal, Tim Miller, Krista A. Ehinger, Benjamin I. P. Rubinstein
2021	J	`jnl`	Local Intrinsic Dimensionality Signals Adversarial Perturbations. CoRR Sandamal Weerasinghe, Tansu Alpcan, Sarah M. Erfani, Christopher Leckie, Benjamin I. P. Rubinstein
2021	J	`jnl`	Machine Learning in Network Anomaly Detection: A Survey. IEEE Access Song Wang, Juan Fernando Balarezo, Sithamparanathan Kandeepan, Akram Al-Hourani, Karina Gomez Chavez, Benjamin I. P. Rubinstein
2021	—	`conf`	Mitigating Data Poisoning in Text Classification with Differential Privacy. EMNLP (Findings) Chang Xu, Jun Wang, Francisco Guzmán, Benjamin I. P. Rubinstein, Trevor Cohn
2021	A*	`conf`	Needle in a Haystack: Label-Efficient Evaluation under Extreme Class Imbalance. KDD Neil G. Marchant, Benjamin I. P. Rubinstein
2021	J	`jnl`	No DBA? No regret! Multi-armed bandits for index tuning of analytical and HTAP workloads with provable guarantees. CoRR R. Malinga Perera, Bastian Oetomo, Benjamin I. P. Rubinstein, Renata Borovica-Gajic
2021	—	`conf`	Putting words into the system's mouth: A targeted attack on neural machine translation using monolingual data poisoning. ACL/IJCNLP (Findings) Jun Wang, Chang Xu, Francisco Guzmán, Ahmed El-Kishky, Yuqing Tang, Benjamin I. P. Rubinstein, Trevor Cohn
2021	J	`jnl`	Putting words into the system's mouth: A targeted attack on neural machine translation using monolingual data poisoning. CoRR Jun Wang, Chang Xu, Francisco Guzmán, Ahmed El-Kishky, Yuqing Tang, Benjamin I. P. Rubinstein, Trevor Cohn
2021	J	`jnl`	State Selection Algorithms and Their Impact on The Performance of Stateful Network Protocol Fuzzing. CoRR Dongge Liu, Van-Thuan Pham, Gidon Ernst, Toby Murray, Benjamin I. P. Rubinstein
2021	—	`conf`	Strategic Mitigation Against Wireless Attacks on Autonomous Platoons. ECML/PKDD (4) Guoxin Sun, Tansu Alpcan, Benjamin I. P. Rubinstein, Seyit Camtepe
2021	J	`jnl`	TRS: Transferability Reduced Ensemble via Encouraging Gradient Diversity and Model Smoothness. CoRR Zhuolin Yang, Linyi Li, Xiaojun Xu, Shiliang Zuo, Qian Chen, Benjamin I. P. Rubinstein, Ce Zhang, Bo Li
2021	A*	`conf`	TRS: Transferability Reduced Ensemble via Promoting Gradient Diversity and Model Smoothness. NeurIPS Zhuolin Yang, Linyi Li, Xiaojun Xu, Shiliang Zuo, Qian Chen, Pan Zhou, Benjamin I. P. Rubinstein, Ce Zhang, Bo Li
2021	A*	`conf`	Towards Systematic and Dynamic Task Allocation for Collaborative Parallel Fuzzing. ASE Van-Thuan Pham, Manh-Dung Nguyen, Quang-Trung Ta, Toby Murray, Benjamin I. P. Rubinstein
2021	J	`jnl`	d-blink: Distributed End-to-End Bayesian Entity Resolution. J. Comput. Graph. Stat. Neil G. Marchant, Andee Kaplan, Daniel N. Elazar, Benjamin I. P. Rubinstein, Rebecca C. Steorts
2020	J	`jnl`	A Graph Symmetrisation Bound on Channel Information Leakage under Blowfish Privacy. CoRR Tobias Edwards, Benjamin I. P. Rubinstein, Zuhe Zhang, Sanming Zhou
2020	J	`jnl`	A general framework for label-efficient online evaluation with asymptotic guarantees. CoRR Neil G. Marchant, Benjamin I. P. Rubinstein
2020	B	`conf`	Adversarial Reinforcement Learning under Partial Observability in Autonomous Computer Network Defence. IJCNN Yi Han, David Hubczenko, Paul Montague, Olivier Y. de Vel, Tamas Abraham, Benjamin I. P. Rubinstein, Christopher Leckie, Tansu Alpcan, Sarah M. Erfani
2020	—	`conf`	Assessing Centrality Without Knowing Connections. PAKDD (2) Leyla Roohi, Benjamin I. P. Rubinstein, Vanessa Teague
2020	J	`jnl`	Assessing Centrality Without Knowing Connections. CoRR Leyla Roohi, Benjamin I. P. Rubinstein, Vanessa Teague
2020	J	`jnl`	DBA bandits: Self-driving index tuning under ad-hoc, analytical workloads with safety guarantees. CoRR Malinga Perera, Bastian Oetomo, Benjamin I. P. Rubinstein, Renata Borovica-Gajic
2020	J	`jnl`	Discrete Few-Shot Learning for Pan Privacy. CoRR Roei Gelbhart, Benjamin I. P. Rubinstein
2020	Misc	`conf`	Function Interpolation for Learned Index Structures. ADC Naufal Fikri Setiawan, Benjamin I. P. Rubinstein, Renata Borovica-Gajic
2020	J	`jnl`	Improving Interpretability of CNN Models Using Non-Negative Concept Activation Vectors. CoRR Ruihan Zhang, Prashan Madumal, Tim Miller, Krista A. Ehinger, Benjamin I. P. Rubinstein
2020	A*	`conf`	LEGION: Best-First Concolic Testing. ASE Dongge Liu, Gidon Ernst, Toby Murray, Benjamin I. P. Rubinstein
2020	B	`conf`	Legion: Best-First Concolic Testing (Competition Contribution). FASE Dongge Liu, Gidon Ernst, Toby Murray, Benjamin I. P. Rubinstein
2020	J	`jnl`	Legion: Best-First Concolic Testing. CoRR Dongge Liu, Gidon Ernst, Toby Murray, Benjamin I. P. Rubinstein
2020	J	`jnl`	Not fit for Purpose: A critical analysis of the 'Five Safes'. CoRR Chris Culnane, Benjamin I. P. Rubinstein, David Watts
2020	B	`conf`	Sampling Without Compromising Accuracy in Adaptive Data Analysis. ALT Benjamin Fish, Lev Reyzin, Benjamin I. P. Rubinstein
2020	J	`jnl`	Targeted Poisoning Attacks on Black-Box Neural Machine Translation. CoRR Chang Xu, Jun Wang, Yuqing Tang, Francisco Guzmán, Benjamin I. P. Rubinstein, Trevor Cohn
2019	J	`jnl`	A Note on Bounding Regret of the C$^2$UCB Contextual Combinatorial Bandit. CoRR Bastian Oetomo, Malinga Perera, Renata Borovica-Gajic, Benjamin I. P. Rubinstein
2019	J	`jnl`	Adversarial Reinforcement Learning under Partial Observability in Software-Defined Networking. CoRR Yi Han, David Hubczenko, Paul Montague, Olivier Y. de Vel, Tamas Abraham, Benjamin I. P. Rubinstein, Christopher Leckie, Tansu Alpcan, Sarah M. Erfani
2019	A*	`conf`	Attacking Data Transforming Learners at Training Time. AAAI Scott Alfeld, Ara Vartanian, Lucas Newman-Johnson, Benjamin I. P. Rubinstein
2019	A*	`conf`	Differentially-Private Two-Party Egocentric Betweenness Centrality. INFOCOM Leyla Roohi, Benjamin I. P. Rubinstein, Vanessa Teague
2019	J	`jnl`	Differentially-Private Two-Party Egocentric Betweenness Centrality. CoRR Leyla Roohi, Benjamin I. P. Rubinstein, Vanessa Teague
2019	A*	`conf`	Exploiting Worker Correlation for Label Aggregation in Crowdsourcing. ICML Yuan Li, Benjamin I. P. Rubinstein, Trevor Cohn
2019	J	`jnl`	Stop the Open Data Bus, We Want to Get Off. CoRR Chris Culnane, Benjamin I. P. Rubinstein, Vanessa Teague
2019	A*	`conf`	Truth Inference at Scale: A Bayesian Model for Adjudicating Highly Redundant Crowd Annotations. WWW Yuan Li, Benjamin I. P. Rubinstein, Trevor Cohn
2019	J	`jnl`	Truth Inference at Scale: A Bayesian Model for Adjudicating Highly Redundant Crowd Annotations. CoRR Yuan Li, Benjamin I. P. Rubinstein, Trevor Cohn
2019	J	`jnl`	d-blink: Distributed End-to-End Bayesian Entity Resolution. CoRR Neil G. Marchant, Rebecca C. Steorts, Andee Kaplan, Benjamin I. P. Rubinstein, Daniel N. Elazar
2018	—	`conf`	Adequacy of the Gradient-Descent Method for Classifier Evasion Attacks. AAAI Workshops Yi Han, Benjamin I. P. Rubinstein
2018	J	`jnl`	Differentially private counting of users' spatial regions. Knowl. Inf. Syst. Maryam Fanaeepour, Benjamin I. P. Rubinstein
2018	—	`conf`	Fast Manifold Landmarking Using Locality-Sensitive Hashing. PAKDD (3) Zay Maung Maung Aye, Benjamin I. P. Rubinstein, Kotagiri Ramamohanarao
2018	A*	`conf`	Histogramming Privately Ever After: Differentially-Private Data-Dependent Error Bound Optimisation. ICDE Maryam Fanaeepour, Benjamin I. P. Rubinstein
2018	J	`jnl`	Options for encoding names for data linking at the Australian Bureau of Statistics. CoRR Chris Culnane, Benjamin I. P. Rubinstein, Vanessa Teague
2018	J	`jnl`	PPFA: Privacy Preserving Fog-Enabled Aggregation in Smart Grid. IEEE Trans. Ind. Informatics Lingjuan Lyu, Karthik Nandakumar, Benjamin I. P. Rubinstein, Jiong Jin, Justin Bedo, Marimuthu Palaniswami
2018	—	`conf`	Reinforcement Learning for Autonomous Defence in Software-Defined Networking. GameSec Yi Han, Benjamin I. P. Rubinstein, Tamas Abraham, Tansu Alpcan, Olivier Y. de Vel, Sarah M. Erfani, David Hubczenko, Christopher Leckie, Paul Montague
2018	J	`jnl`	Reinforcement Learning for Autonomous Defence in Software-Defined Networking. CoRR Yi Han, Benjamin I. P. Rubinstein, Tamas Abraham, Tansu Alpcan, Olivier Y. de Vel, Sarah M. Erfani, David Hubczenko, Christopher Leckie, Paul Montague
2018	Misc	`conf`	Sublinear-Time Adaptive Data Analysis. ISAIM Benjamin Fish, Lev Reyzin, Benjamin I. P. Rubinstein
2017	J	`jnl`	Adequacy of the Gradient-Descent Method for Classifier Evasion Attacks. CoRR Yi Han, Benjamin I. P. Rubinstein
2017	J	`jnl`	Differential Privacy for Bayesian Inference through Posterior Sampling. J. Mach. Learn. Res. Christos Dimitrakakis, Blaine Nelson, Zuhe Zhang, Aikaterini Mitrokotsa, Benjamin I. P. Rubinstein
2017	B	`conf`	E-Storm: Replication-Based State Management in Distributed Stream Processing Systems. ICPP Xunyun Liu, Aaron Harwood, Shanika Karunasekera, Benjamin I. P. Rubinstein, Rajkumar Buyya
2017	J	`jnl`	End-to-End Differentially-Private Parameter Tuning in Spatial Histograms. CoRR Maryam Fanaeepour, Benjamin I. P. Rubinstein
2017	J	`jnl`	Health Data in an Open World. CoRR Chris Culnane, Benjamin I. P. Rubinstein, Vanessa Teague
2017	J	`jnl`	In Search of an Entity Resolution OASIS: Optimal Asymptotic Sequential Importance Sampling. CoRR Neil G. Marchant, Benjamin I. P. Rubinstein
2017	J	`jnl`	In Search of an Entity Resolution OASIS: Optimal Asymptotic Sequential Importance Sampling. Proc. VLDB Endow. Neil G. Marchant, Benjamin I. P. Rubinstein
2017	A*	`conf`	Pain-Free Random Differential Privacy with Sensitivity Sampling. ICML Benjamin I. P. Rubinstein, Francesco Aldà
2017	J	`jnl`	Pain-Free Random Differential Privacy with Sensitivity Sampling. CoRR Benjamin I. P. Rubinstein, Francesco Aldà
2017	J	`jnl`	Privacy Assessment of De-identified Opal Data: A report for Transport for NSW. CoRR Chris Culnane, Benjamin I. P. Rubinstein, Vanessa Teague
2017	J	`jnl`	Sublinear-Time Adaptive Data Analysis. CoRR Benjamin Fish, Lev Reyzin, Benjamin I. P. Rubinstein
2017	A*	`conf`	The Bernstein Mechanism: Function Release under Differential Privacy. AAAI Francesco Aldà, Benjamin I. P. Rubinstein
2017	J	`jnl`	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. CoRR Chris Culnane, Benjamin I. P. Rubinstein, Vanessa Teague
2016	J	`jnl`	A Game Theoretical Approach to Defend Against Co-Resident Attacks in Cloud Computing: Preventing Co-Residence Using Semi-Supervised Learning. IEEE Trans. Inf. Forensics Secur. Yi Han, Tansu Alpcan, Jeffrey Chan, Christopher Leckie, Benjamin I. P. Rubinstein
2016	A*	`conf`	Beyond Points and Paths: Counting Private Bodies. ICDM Maryam Fanaeepour, Benjamin I. P. Rubinstein
2016	J	`jnl`	Beyond Points and Paths: Counting Private Bodies. CoRR Maryam Fanaeepour, Benjamin I. P. Rubinstein
2016	B	`conf`	Fast trajectory clustering using Hashing methods. IJCNN Iván Sánchez, Zay Maung Maung Aye, Benjamin I. P. Rubinstein, Kotagiri Ramamohanarao
2016	B	`conf`	Large Scale Metric learning. IJCNN Zay Maung Maung Aye, Kotagiri Ramamohanarao, Benjamin I. P. Rubinstein
2016	J	`jnl`	Large-Scale Strategic Games and Adversarial Machine Learning. CoRR Tansu Alpcan, Benjamin I. P. Rubinstein, Christopher Leckie
2016	—	`conf`	Large-scale strategic games and adversarial machine learning. CDC Tansu Alpcan, Benjamin I. P. Rubinstein, Christopher Leckie
2016	A*	`conf`	MOOCs Meet Measurement Theory: A Topic-Modelling Approach. AAAI Jiazhen He, Benjamin I. P. Rubinstein, James Bailey, Rui Zhang, Sandra Milligan, Jeffrey Chan
2016	A*	`conf`	On the Differential Privacy of Bayesian Inference. AAAI Zuhe Zhang, Benjamin I. P. Rubinstein, Christos Dimitrakakis
2016	J	`jnl`	TopicResponse: A Marriage of Topic Modelling and Rasch Modelling for Automatic Measurement in MOOCs. CoRR Jiazhen He, Rui Zhang, James Bailey, Benjamin I. P. Rubinstein, Sandra Milligan
2016	A	`conf`	Validity: a framework for cross-disciplinary collaboration in mining indicators of learning from MOOC forums. LAK Sandra Milligan, Jiazhen He, James Bailey, Rui Zhang, Benjamin I. P. Rubinstein
2015	A*	`conf`	Identifying At-Risk Students in Massive Open Online Courses. AAAI Jiazhen He, James Bailey, Benjamin I. P. Rubinstein, Rui Zhang
2015	J	`jnl`	MOOCs Meet Measurement Theory: A Topic-Modelling Approach. CoRR Jiazhen He, Benjamin I. P. Rubinstein, James Bailey, Rui Zhang, Sandra Milligan, Jeffrey Chan
2015	J	`jnl`	On the Differential Privacy of Bayesian Inference. CoRR Zuhe Zhang, Benjamin I. P. Rubinstein, Christos Dimitrakakis
2015	J	`jnl`	Principled Graph Matching Algorithms for Integrating Multiple Data Sources. IEEE Trans. Knowl. Data Eng. Duo Zhang, Benjamin I. P. Rubinstein, Jim Gemmell
2015	A*	`conf`	Sub-Merge: Diving Down to the Attribute-Value Level in Statistical Schema Matching. AAAI Zhe Lim, Benjamin I. P. Rubinstein
2015	J	`jnl`	The CASE histogram: privacy-aware processing of trajectory data using aggregates. GeoInformatica Maryam Fanaeepour, Lars Kulik, Egemen Tanin, Benjamin I. P. Rubinstein
2014	J	`jnl`	Bounding Embeddings of VC Classes into Maximum Classes. CoRR J. Hyam Rubinstein, Benjamin I. P. Rubinstein, Peter L. Bartlett
2014	J	`jnl`	Principled Graph Matching Algorithms for Integrating Multiple Data Sources. CoRR Duo Zhang, Benjamin I. P. Rubinstein, Jim Gemmell
2014	—	`ed.`	Proceedings of the 2014 Workshop on Artificial Intelligent and Security Workshop, AISec 2014, Scottsdale, AZ, USA, November 7, 2014 AISec@CCS Christos Dimitrakakis, Aikaterini Mitrokotsa, Benjamin I. P. Rubinstein, Gail-Joon Ahn
2014	B	`conf`	Robust and Private Bayesian Inference. ALT Christos Dimitrakakis, Blaine Nelson, Aikaterini Mitrokotsa, Benjamin I. P. Rubinstein
2014	J	`jnl`	Security Evaluation of Support Vector Machines in Adversarial Environments. CoRR Battista Biggio, Igino Corona, Blaine Nelson, Benjamin I. P. Rubinstein, Davide Maiorca, Giorgio Fumera, Giorgio Giacinto, Fabio Roli
2014	A*	`conf`	Workshop Summary of AISec'14: 2014 Workshop on Artificial Intelligent and Security. CCS Christos Dimitrakakis, Aikaterini Mitrokotsa, Benjamin I. P. Rubinstein
2013	—	`conf`	On the challenges of balancing privacy and utility of open health data. AIIP/Semantic Cities@IJCAI Christian Guttmann, Xingzhi Sun, Chaitanya Rao, Carlos Queiroz, Benjamin I. P. Rubinstein
2013	J	`jnl`	Robust, Secure and Private Bayesian Inference. CoRR Christos Dimitrakakis, Blaine Nelson, Aikaterini Mitrokotsa, Benjamin I. P. Rubinstein
2012	J	`jnl`	A Bayesian Approach to Discovering Truth from Conflicting Sources for Data Integration CoRR Bo Zhao, Benjamin I. P. Rubinstein, Jim Gemmell, Jiawei Han
2012	J	`jnl`	A Bayesian Approach to Discovering Truth from Conflicting Sources for Data Integration. Proc. VLDB Endow. Bo Zhao, Benjamin I. P. Rubinstein, Jim Gemmell, Jiawei Han
2012	J	`jnl`	A Geometric Approach to Sample Compression. J. Mach. Learn. Res. Benjamin I. P. Rubinstein, J. Hyam Rubinstein
2012	J	`jnl`	A Learning-Based Approach to Reactive Security. IEEE Trans. Dependable Secur. Comput. Adam Barth, Benjamin I. P. Rubinstein, Mukund Sundararajan, John C. Mitchell, Dawn Song, Peter L. Bartlett
2012	A*	`conf`	Fifth ACM workshop on artificial intelligence and security (AISec 2012). CCS Alvaro A. Cárdenas, Blaine Nelson, Benjamin I. P. Rubinstein
2012	J	`jnl`	Learning in a Large Function Space: Privacy-Preserving Mechanisms for SVM Learning. J. Priv. Confidentiality Benjamin I. P. Rubinstein, Peter L. Bartlett, Ling Huang, Nina Taft
2012	J	`jnl`	On the Stability of Empirical Risk Minimization in the Presence of Multiple Risk Minimizers. IEEE Trans. Inf. Theory Benjamin I. P. Rubinstein, Aleksandr Simma
2012	J	`jnl`	Query Strategies for Evading Convex-Inducing Classifiers. J. Mach. Learn. Res. Blaine Nelson, Benjamin I. P. Rubinstein, Ling Huang, Anthony D. Joseph, Steven J. Lee, Satish Rao, J. D. Tygar
2012	J	`jnl`	Scaling Multiple-Source Entity Resolution using Statistically Efficient Transfer Learning CoRR Sahand Negahban, Benjamin I. P. Rubinstein, Jim Gemmell
2012	A	`conf`	Scaling multiple-source entity resolution using statistically efficient transfer learning. CIKM Sahand Negahban, Benjamin I. P. Rubinstein, Jim Gemmell
2011	—	`conf`	Adversarial machine learning. AISec Ling Huang, Anthony D. Joseph, Blaine Nelson, Benjamin I. P. Rubinstein, J. D. Tygar
2011	J	`jnl`	How Open Should Open Source Be? CoRR Adam Barth, Saung Li, Benjamin I. P. Rubinstein, Dawn Song
2011	J	`jnl`	Improving Entity Resolution with Global Constraints CoRR Jim Gemmell, Benjamin I. P. Rubinstein, Ashok K. Chandra
2011	J	`jnl`	Link Prediction by De-anonymization: How We Won the Kaggle Social Network Challenge CoRR Arvind Narayanan, Elaine Shi, Benjamin I. P. Rubinstein
2011	B	`conf`	Link prediction by de-anonymization: How We Won the Kaggle Social Network Challenge. IJCNN Arvind Narayanan, Elaine Shi, Benjamin I. P. Rubinstein
2011	—	`ed.`	Proceedings of the 4th ACM Workshop on Security and Artificial Intelligence, AISec 2011, Chicago, IL, USA, October 21, 2011 AISec Yan Chen, Alvaro A. Cárdenas, Rachel Greenstadt, Benjamin I. P. Rubinstein
2010	—	`conf`	A Learning-Based Approach to Reactive Security. Financial Cryptography Adam Barth, Benjamin I. P. Rubinstein, Mukund Sundararajan, John C. Mitchell, Dawn Song, Peter L. Bartlett
2010	—	`conf`	Classifier Evasion: Models and Open Problems. PSDML Blaine Nelson, Benjamin I. P. Rubinstein, Ling Huang, Anthony D. Joseph, J. D. Tygar
2010	J	`jnl`	Corrigendum to "Shifting: One-inclusion mistake bounds and sample compression" [J. Comput. System Sci 75 (1) (2009) 37-59]. J. Comput. Syst. Sci. Benjamin I. P. Rubinstein, Peter L. Bartlett, J. Hyam Rubinstein
2010	J	`jnl`	Near-Optimal Evasion of Convex-Inducing Classifiers CoRR Blaine Nelson, Benjamin I. P. Rubinstein, Ling Huang, Anthony D. Joseph, Shing-Hon Lau, Steven J. Lee, Satish Rao, Anthony Tran, J. D. Tygar
2010	A	`conf`	Near-Optimal Evasion of Convex-Inducing Classifiers. AISTATS Blaine Nelson, Benjamin I. P. Rubinstein, Ling Huang, Anthony D. Joseph, Shing-Hon Lau, Steven J. Lee, Satish Rao, Anthony Tran, J. Doug Tygar
2010	J	`jnl`	On the Stability of Empirical Risk Minimization in the Presence of Multiple Risk Minimizers CoRR Benjamin I. P. Rubinstein, Aleksandr Simma
2010	J	`jnl`	Query Strategies for Evading Convex-Inducing Classifiers CoRR Blaine Nelson, Benjamin I. P. Rubinstein, Ling Huang, Anthony D. Joseph, Steven J. Lee, Satish Rao, J. D. Tygar
2010	—	`—`	Secure Learning and Learning for Security: Research in the Intersection. Benjamin I. P. Rubinstein
2009	J	`jnl`	A Geometric Approach to Sample Compression CoRR Benjamin I. P. Rubinstein, J. Hyam Rubinstein
2009	J	`jnl`	A Learning-Based Approach to Reactive Security CoRR Adam Barth, Benjamin I. P. Rubinstein, Mukund Sundararajan, John C. Mitchell, Dawn Xiaodong Song, Peter L. Bartlett
2009	A	`conf`	ANTIDOTE: understanding and defending against poisoning of anomaly detectors. Internet Measurement Conference Benjamin I. P. Rubinstein, Blaine Nelson, Ling Huang, Anthony D. Joseph, Shing-Hon Lau, Satish Rao, Nina Taft, J. D. Tygar
2009	A*	`conf`	Adaptive bidding for display advertising. WWW Arpita Ghosh, Benjamin I. P. Rubinstein, Sergei Vassilvitskii, Martin Zinkevich
2009	J	`jnl`	Learning in a Large Function Space: Privacy-Preserving Mechanisms for SVM Learning CoRR Benjamin I. P. Rubinstein, Peter L. Bartlett, Ling Huang, Nina Taft
2009	J	`jnl`	Shifting: One-inclusion mistake bounds and sample compression. J. Comput. Syst. Sci. Benjamin I. P. Rubinstein, Peter L. Bartlett, J. Hyam Rubinstein
2009	J	`jnl`	Stealthy poisoning attacks on PCA-based anomaly detectors. SIGMETRICS Perform. Evaluation Rev. Benjamin I. P. Rubinstein, Blaine Nelson, Ling Huang, Anthony D. Joseph, Shing-Hon Lau, Satish Rao, Nina Taft, J. D. Tygar
2008	A	`conf`	Evading Anomaly Detection through Variance Injection Attacks on PCA. RAID Benjamin I. P. Rubinstein, Blaine Nelson, Ling Huang, Anthony D. Joseph, Shing-Hon Lau, Nina Taft, J. Doug Tygar
2008	—	`conf`	Exploiting Machine Learning to Subvert Your Spam Filter. LEET Blaine Nelson, Marco Barreno, Fuching Jack Chi, Anthony D. Joseph, Benjamin I. P. Rubinstein, Udam Saini, Charles Sutton, J. Doug Tygar, Kai Xia
2008	A*	`conf`	Geometric & Topological Representations of Maximum Classes with Applications to Sample Compression. COLT J. Hyam Rubinstein, Benjamin I. P. Rubinstein
2008	—	`conf`	Open problems in the security of learning. AISec Marco Barreno, Peter L. Bartlett, Fuching Jack Chi, Anthony D. Joseph, Blaine Nelson, Benjamin I. P. Rubinstein, Udam Saini, J. Doug Tygar
2006	—	`conf`	Shifting, One-Inclusion Mistake Bounds and Tight Multiclass Expected Risk Bounds. NIPS Benjamin I. P. Rubinstein, Peter L. Bartlett, J. Hyam Rubinstein
2003	J	`jnl`	Machine learning in low-level microarray analysis. SIGKDD Explor. Benjamin I. P. Rubinstein, Jon D. McAuliffe, Simon Cawley, Marimuthu Palaniswami, Kotagiri Ramamohanarao, Terence P. Speed
2001	B	`conf`	Evolving quantum circuits using genetic programming. CEC Benjamin I. P. Rubinstein