Benjamin I. P. Rubinstein

ORCID

Publication Activity (10 Years)

Years Active: 2001-2024
Publications (10 Years): 121

Top Venues

University of California, Berkeley, USA (PHD)

Education History

University of California, Berkeley, USA

PHD

Publications

Neil G. Marchant, Benjamin I. P. Rubinstein
Adaptive Data Analysis for Growing Data. CoRR (2024)
Guoxin Sun, Tansu Alpcan, Benjamin I. P. Rubinstein, Seyit Camtepe
To Act or Not to Act: An Adversarial Game for Securing Vehicle Platoons. IEEE Trans. Inf. Forensics Secur. 19 (2024)
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
Mitigating Challenges of the Space Environment for Onboard Artificial Intelligence: Design Overview of the Imaging Payload on SpIRIT. CoRR (2024)
Jiankai Jin, Chitchanok Chuengsatiansup, Toby Murray, Benjamin I. P. Rubinstein, Yuval Yarom, Olga Ohrimenko
Elephants Do Not Forget: Differential Privacy with State Continuity for Privacy Budget. CoRR (2024)
Aref Miri Rekavandi, Olga Ohrimenko, Benjamin I. P. Rubinstein
RS-Reg: Probabilistic and Robust Certified Regression Through Randomized Smoothing. CoRR (2024)
Xuanli He, Jun Wang, Qiongkai Xu, Pasquale Minervini, Pontus Stenetorp, Benjamin I. P. Rubinstein, Trevor Cohn
Transferring Troubles: Cross-Lingual Transferability of Backdoor Attacks in LLMs with Instruction Tuning. CoRR (2024)
Xuanli He, Qiongkai Xu, Jun Wang, Benjamin I. P. Rubinstein, Trevor Cohn
SEEP: Training Dynamics Grounds Latent Representation Search for Mitigating Backdoor Poisoning Attacks. CoRR (2024)
Jun Wang, Qiongkai Xu, Xuanli He, Benjamin I. P. Rubinstein, Trevor Cohn
Backdoor Attack on Multilingual Machine Translation. CoRR (2024)
Jun Wang, Qiongkai Xu, Xuanli He, Benjamin I. P. Rubinstein, Trevor Cohn
Backdoor Attacks on Multilingual Machine Translation. NAACL-HLT (2024)
Xuanli He, Qiongkai Xu, Jun Wang, Benjamin I. P. Rubinstein, Trevor Cohn
Mitigating Backdoor Poisoning Attacks through the Lens of Spurious Correlation. EMNLP (2023)
R. Malinga Perera, Bastian Oetomo, Benjamin I. P. Rubinstein, Renata Borovica-Gajic
No DBA? No Regret! Multi-Armed Bandits for Index Tuning of Analytical and HTAP Workloads With Provable Guarantees. IEEE Trans. Knowl. Data Eng. 35 (12) (2023)
Shijie Liu, Andrew C. Cullen, Paul Montague, Sarah M. Erfani, Benjamin I. P. Rubinstein
Enhancing the Antidote: Improved Pointwise Certifications against Poisoning Attacks. CoRR (2023)
Guoxin Sun, Tansu Alpcan, Seyit Camtepe, Andrew C. Cullen, Benjamin I. P. Rubinstein
An Adversarial Strategic Game for Machine Learning as a Service using System Features. AAMAS (2023)
Andrew C. Cullen, Paul Montague, Shijie Liu, Sarah M. Erfani, Benjamin I. P. Rubinstein
It's Simplex! Disaggregating Measures to Improve Certified Robustness. CoRR (2023)
Guanli Liu, Jianzhong Qi, Lars Kulik, Kazuya Soga, Renata Borovica-Gajic, Benjamin I. P. Rubinstein
Efficient Index Learning via Model Reuse and Fine-tuning. ICDEW (2023)
Xuanli He, Jun Wang, Benjamin I. P. Rubinstein, Trevor Cohn
IMBERT: Making BERT Immune to Insertion-based Backdoor Attacks. CoRR (2023)
Wentao Gao, Van-Thuan Pham, Dongge Liu, Oliver Chang, Toby Murray, Benjamin I. P. Rubinstein
Beyond the Coverage Plateau: A Comprehensive Study of Fuzz Blockers (Registered Report). FUZZING (2023)
Xuanli He, Qiongkai Xu, Jun Wang, Benjamin I. P. Rubinstein, Trevor Cohn
Mitigating Backdoor Poisoning Attacks through the Lens of Spurious Correlation. CoRR (2023)
Zhuoqun Huang, Neil G. Marchant, Keane Lucas, Lujo Bauer, Olga Ohrimenko, Benjamin I. P. Rubinstein
Certified Robustness of Learning-based Static Malware Detectors. CoRR (2023)
Andrew C. Cullen, Benjamin I. P. Rubinstein, Sithamparanathan Kandeepan, Barry Flower, Philip H. W. Leong
Predicting dynamic spectrum allocation: a review covering simulation, modelling, and prediction. Artif. Intell. Rev. 56 (10) (2023)
Neil G. Marchant, Benjamin I. P. Rubinstein, Rebecca C. Steorts
Bayesian Graphical Entity Resolution Using Exchangeable Random Partition Priors. CoRR (2023)
Zhuoqun Huang, Neil G. Marchant, Keane Lucas, Lujo Bauer, Olga Ohrimenko, Benjamin I. P. Rubinstein
RS-Del: Edit Distance Robustness Certificates for Sequence Classifiers via Randomized Deletion. NeurIPS (2023)
Bastian Oetomo, R. Malinga Perera, Renata Borovica-Gajic, Benjamin I. P. Rubinstein
Cutting to the chase with warm-start contextual bandits. Knowl. Inf. Syst. 65 (9) (2023)
Shijie Liu, Andrew C. Cullen, Paul Montague, Sarah M. Erfani, Benjamin I. P. Rubinstein
Enhancing the Antidote: Improved Pointwise Certifications against Poisoning Attacks. AAAI (2023)
Andrew C. Cullen, Paul Montague, Shijie Liu, Sarah M. Erfani, Benjamin I. P. Rubinstein
Exploiting Certified Defences to Attack Randomised Smoothing. CoRR (2023)
Andrew C. Cullen, Paul Montague, Shijie Liu, Sarah M. Erfani, Benjamin I. P. Rubinstein
Double Bubble, Toil and Trouble: Enhancing Certified Robustness through Transitivity. NeurIPS (2022)
Joachim Hyam Rubinstein, Benjamin I. P. Rubinstein
Unlabelled Sample Compression Schemes for Intersection-Closed Classes and Extremal Classes. NeurIPS (2022)
Dongge Liu, Van-Thuan Pham, Gidon Ernst, Toby Murray, Benjamin I. P. Rubinstein
State Selection Algorithms and Their Impact on The Performance of Stateful Network Protocol Fuzzing. SANER (2022)
Jun Wang, Xuanli He, Benjamin I. P. Rubinstein, Trevor Cohn
Foiling Training-Time Attacks on Neural Machine Translation Systems. EMNLP (Findings) (2022)
Matthias Bachfischer, Renata Borovica-Gajic, Benjamin I. P. Rubinstein
Testing the Robustness of Learned Index Structures. CoRR (2022)
Sandamal Weerasinghe, Tamas Abraham, Tansu Alpcan, Sarah M. Erfani, Christopher Leckie, Benjamin I. P. Rubinstein
Local Intrinsic Dimensionality Signals Adversarial Perturbations. CDC (2022)
R. Malinga Perera, Bastian Oetomo, Benjamin I. P. Rubinstein, Renata Borovica-Gajic
HMAB: Self-Driving Hierarchy of Bandits for Integrated Physical Database Design Tuning. Proc. VLDB Endow. 16 (2) (2022)
Neil G. Marchant, Benjamin I. P. Rubinstein, Scott Alfeld
Hard to Forget: Poisoning Attacks on Certified Machine Unlearning. AAAI (2022)
Guoxin Sun, Tansu Alpcan, Benjamin I. P. Rubinstein, Seyit Camtepe
Securing Cyber-Physical Systems: Physics-Enhanced Adversarial Learning for Autonomous Platoons. ECML/PKDD (3) (2022)
Tobias Edwards, Benjamin I. P. Rubinstein, Zuhe Zhang, Sanming Zhou
A Graph Symmetrization Bound on Channel Information Leakage Under Blowfish Privacy. IEEE Trans. Inf. Theory 68 (1) (2022)
Andrew C. Cullen, Paul Montague, Shijie Liu, Sarah M. Erfani, Benjamin I. P. Rubinstein
Double Bubble, Toil and Trouble: Enhancing Certified Robustness through Transitivity. CoRR (2022)
Jun Wang, Benjamin I. P. Rubinstein, Trevor Cohn
Measuring and Mitigating Name Biases in Neural Machine Translation. ACL (1) (2022)
Jiankai Jin, Eleanor McMurtry, Benjamin I. P. Rubinstein, Olga Ohrimenko
Are We There Yet? Timing and Floating-Point Attacks on Differential Privacy Systems. IEEE Symposium on Security and Privacy (2022)
J. Hyam Rubinstein, Benjamin I. P. Rubinstein
Unlabelled Sample Compression Schemes for Intersection-Closed Classes and Extremal Classes. CoRR (2022)
Jiankai Jin, Olga Ohrimenko, Benjamin I. P. Rubinstein
Getting a-Round Guarantees: Floating-Point Attacks on Certified Robustness. CoRR (2022)
Ruihan Zhang, Prashan Madumal, Tim Miller, Krista A. Ehinger, Benjamin I. P. Rubinstein
Invertible Concept-based Explanations for CNN Models with Non-negative Concept Activation Vectors. AAAI (2021)
Zhuolin Yang, Linyi Li, Xiaojun Xu, Shiliang Zuo, Qian Chen, Pan Zhou, Benjamin I. P. Rubinstein, Ce Zhang, Bo Li
TRS: Transferability Reduced Ensemble via Promoting Gradient Diversity and Model Smoothness. NeurIPS (2021)
Guoxin Sun, Tansu Alpcan, Benjamin I. P. Rubinstein, Seyit Camtepe
A Communication Security Game on Switched Systems for Autonomous Vehicle Platoons. CoRR (2021)
Chang Xu, Jun Wang, Yuqing Tang, Francisco Guzmán, Benjamin I. P. Rubinstein, Trevor Cohn
A Targeted Attack on Black-Box Neural Machine Translation with Parallel Data Poisoning. WWW (2021)
Sandamal Weerasinghe, Tansu Alpcan, Sarah M. Erfani, Christopher Leckie, Benjamin I. P. Rubinstein
Local Intrinsic Dimensionality Signals Adversarial Perturbations. CoRR (2021)
Guoxin Sun, Tansu Alpcan, Benjamin I. P. Rubinstein, Seyit Camtepe
Strategic Mitigation Against Wireless Attacks on Autonomous Platoons. ECML/PKDD (4) (2021)
Bastian Oetomo, R. Malinga Perera, Renata Borovica-Gajic, Benjamin I. P. Rubinstein
Cutting to the Chase with Warm-Start Contextual Bandits. ICDM (2021)
Neil G. Marchant, Benjamin I. P. Rubinstein
Needle in a Haystack: Label-Efficient Evaluation under Extreme Class Imbalance. KDD (2021)
Jiankai Jin, Eleanor McMurtry, Benjamin I. P. Rubinstein, Olga Ohrimenko
Are We There Yet? Timing and Floating-Point Attacks on Differential Privacy Systems. CoRR (2021)
Sandamal Weerasinghe, Tamas Abraham, Tansu Alpcan, Sarah M. Erfani, Christopher Leckie, Benjamin I. P. Rubinstein
Closing the BIG-LID: An Effective Local Intrinsic Dimensionality Defense for Nonlinear Regression Poisoning. IJCAI (2021)
R. Malinga Perera, Bastian Oetomo, Benjamin I. P. Rubinstein, Renata Borovica-Gajic
DBA bandits: Self-driving index tuning under ad-hoc, analytical workloads with safety guarantees. ICDE (2021)
Van-Thuan Pham, Manh-Dung Nguyen, Quang-Trung Ta, Toby Murray, Benjamin I. P. Rubinstein
Towards Systematic and Dynamic Task Allocation for Collaborative Parallel Fuzzing. ASE (2021)
Jun Wang, Chang Xu, Francisco Guzmán, Ahmed El-Kishky, Benjamin I. P. Rubinstein, Trevor Cohn
As Easy as 1, 2, 3: Behavioural Testing of NMT Systems for Numerical Translation. CoRR (2021)
Jun Wang, Chang Xu, Francisco Guzmán, Ahmed El-Kishky, Yuqing Tang, Benjamin I. P. Rubinstein, Trevor Cohn
Putting words into the system's mouth: A targeted attack on neural machine translation using monolingual data poisoning. ACL/IJCNLP (Findings) (2021)
Jun Wang, Chang Xu, Francisco Guzmán, Ahmed El-Kishky, Benjamin I. P. Rubinstein, Trevor Cohn
As Easy as 1, 2, 3: Behavioural Testing of NMT Systems for Numerical Translation. ACL/IJCNLP (Findings) (2021)
Guoxin Sun, Tansu Alpcan, Benjamin I. P. Rubinstein, Seyit Camtepe
A Communication Security Game on Switched Systems for Autonomous Vehicle Platoons. CDC (2021)
Dongge Liu, Van-Thuan Pham, Gidon Ernst, Toby Murray, Benjamin I. P. Rubinstein
State Selection Algorithms and Their Impact on The Performance of Stateful Network Protocol Fuzzing. CoRR (2021)
Zhuolin Yang, Linyi Li, Xiaojun Xu, Shiliang Zuo, Qian Chen, Benjamin I. P. Rubinstein, Ce Zhang, Bo Li
TRS: Transferability Reduced Ensemble via Encouraging Gradient Diversity and Model Smoothness. CoRR (2021)
Neil G. Marchant, Benjamin I. P. Rubinstein, Scott Alfeld
Hard to Forget: Poisoning Attacks on Certified Machine Unlearning. CoRR (2021)
R. Malinga Perera, Bastian Oetomo, Benjamin I. P. Rubinstein, Renata Borovica-Gajic
No DBA? No regret! Multi-armed bandits for index tuning of analytical and HTAP workloads with provable guarantees. CoRR (2021)
Jun Wang, Chang Xu, Francisco Guzmán, Ahmed El-Kishky, Yuqing Tang, Benjamin I. P. Rubinstein, Trevor Cohn
Putting words into the system's mouth: A targeted attack on neural machine translation using monolingual data poisoning. CoRR (2021)
Chang Xu, Jun Wang, Francisco Guzmán, Benjamin I. P. Rubinstein, Trevor Cohn
Mitigating Data Poisoning in Text Classification with Differential Privacy. EMNLP (Findings) (2021)
Neil G. Marchant, Andee Kaplan, Daniel N. Elazar, Benjamin I. P. Rubinstein, Rebecca C. Steorts
d-blink: Distributed End-to-End Bayesian Entity Resolution. J. Comput. Graph. Stat. 30 (2) (2021)
Leyla Roohi, Benjamin I. P. Rubinstein, Vanessa Teague
Assessing Centrality Without Knowing Connections. CoRR (2020)
Chang Xu, Jun Wang, Yuqing Tang, Francisco Guzmán, Benjamin I. P. Rubinstein, Trevor Cohn
Targeted Poisoning Attacks on Black-Box Neural Machine Translation. CoRR (2020)
Roei Gelbhart, Benjamin I. P. Rubinstein
Discrete Few-Shot Learning for Pan Privacy. CoRR (2020)
Tobias Edwards, Benjamin I. P. Rubinstein, Zuhe Zhang, Sanming Zhou
A Graph Symmetrisation Bound on Channel Information Leakage under Blowfish Privacy. CoRR (2020)
Naufal Fikri Setiawan, Benjamin I. P. Rubinstein, Renata Borovica-Gajic
Function Interpolation for Learned Index Structures. ADC (2020)
Dongge Liu, Gidon Ernst, Toby Murray, Benjamin I. P. Rubinstein
LEGION: Best-First Concolic Testing. ASE (2020)
Dongge Liu, Gidon Ernst, Toby Murray, Benjamin I. P. Rubinstein
Legion: Best-First Concolic Testing (Competition Contribution). FASE (2020)
Yi Han, David Hubczenko, Paul Montague, Olivier Y. de Vel, Tamas Abraham, Benjamin I. P. Rubinstein, Christopher Leckie, Tansu Alpcan, Sarah M. Erfani
Adversarial Reinforcement Learning under Partial Observability in Autonomous Computer Network Defence. IJCNN (2020)
Benjamin Fish, Lev Reyzin, Benjamin I. P. Rubinstein
Sampling Without Compromising Accuracy in Adaptive Data Analysis. ALT (2020)
Chris Culnane, Benjamin I. P. Rubinstein, David Watts
Not fit for Purpose: A critical analysis of the 'Five Safes'. CoRR (2020)
Dongge Liu, Gidon Ernst, Toby Murray, Benjamin I. P. Rubinstein
Legion: Best-First Concolic Testing. CoRR (2020)
Leyla Roohi, Benjamin I. P. Rubinstein, Vanessa Teague
Assessing Centrality Without Knowing Connections. PAKDD (2) (2020)
Malinga Perera, Bastian Oetomo, Benjamin I. P. Rubinstein, Renata Borovica-Gajic
DBA bandits: Self-driving index tuning under ad-hoc, analytical workloads with safety guarantees. CoRR (2020)
Ruihan Zhang, Prashan Madumal, Tim Miller, Krista A. Ehinger, Benjamin I. P. Rubinstein
Improving Interpretability of CNN Models Using Non-Negative Concept Activation Vectors. CoRR (2020)
Neil G. Marchant, Benjamin I. P. Rubinstein
A general framework for label-efficient online evaluation with asymptotic guarantees. CoRR (2020)
Leyla Roohi, Benjamin I. P. Rubinstein, Vanessa Teague
Differentially-Private Two-Party Egocentric Betweenness Centrality. CoRR (2019)
Scott Alfeld, Ara Vartanian, Lucas Newman-Johnson, Benjamin I. P. Rubinstein
Attacking Data Transforming Learners at Training Time. AAAI (2019)
Neil G. Marchant, Rebecca C. Steorts, Andee Kaplan, Benjamin I. P. Rubinstein, Daniel N. Elazar
d-blink: Distributed End-to-End Bayesian Entity Resolution. CoRR (2019)
Leyla Roohi, Benjamin I. P. Rubinstein, Vanessa Teague
Differentially-Private Two-Party Egocentric Betweenness Centrality. INFOCOM (2019)
Yi Han, David Hubczenko, Paul Montague, Olivier Y. de Vel, Tamas Abraham, Benjamin I. P. Rubinstein, Christopher Leckie, Tansu Alpcan, Sarah M. Erfani
Adversarial Reinforcement Learning under Partial Observability in Software-Defined Networking. CoRR (2019)
Chris Culnane, Benjamin I. P. Rubinstein, Vanessa Teague
Stop the Open Data Bus, We Want to Get Off. CoRR (2019)
Yuan Li, Benjamin I. P. Rubinstein, Trevor Cohn
Exploiting Worker Correlation for Label Aggregation in Crowdsourcing. ICML (2019)
Yuan Li, Benjamin I. P. Rubinstein, Trevor Cohn
Truth Inference at Scale: A Bayesian Model for Adjudicating Highly Redundant Crowd Annotations. CoRR (2019)
Yuan Li, Benjamin I. P. Rubinstein, Trevor Cohn
Truth Inference at Scale: A Bayesian Model for Adjudicating Highly Redundant Crowd Annotations. WWW (2019)
Bastian Oetomo, Malinga Perera, Renata Borovica-Gajic, Benjamin I. P. Rubinstein
A Note on Bounding Regret of the C$^2$UCB Contextual Combinatorial Bandit. CoRR (2019)
Yi Han, Benjamin I. P. Rubinstein, Tamas Abraham, Tansu Alpcan, Olivier Y. de Vel, Sarah M. Erfani, David Hubczenko, Christopher Leckie, Paul Montague
Reinforcement Learning for Autonomous Defence in Software-Defined Networking. GameSec (2018)
Zay Maung Maung Aye, Benjamin I. P. Rubinstein, Kotagiri Ramamohanarao
Fast Manifold Landmarking Using Locality-Sensitive Hashing. PAKDD (3) (2018)
Maryam Fanaeepour, Benjamin I. P. Rubinstein
Differentially private counting of users' spatial regions. Knowl. Inf. Syst. 54 (1) (2018)
Yi Han, Benjamin I. P. Rubinstein
Adequacy of the Gradient-Descent Method for Classifier Evasion Attacks. AAAI Workshops (2018)
Yi Han, Benjamin I. P. Rubinstein, Tamas Abraham, Tansu Alpcan, Olivier Y. de Vel, Sarah M. Erfani, David Hubczenko, Christopher Leckie, Paul Montague
Reinforcement Learning for Autonomous Defence in Software-Defined Networking. CoRR (2018)
Chris Culnane, Benjamin I. P. Rubinstein, Vanessa Teague
Options for encoding names for data linking at the Australian Bureau of Statistics. CoRR (2018)
Lingjuan Lyu, Karthik Nandakumar, Benjamin I. P. Rubinstein, Jiong Jin, Justin Bedo, Marimuthu Palaniswami
PPFA: Privacy Preserving Fog-Enabled Aggregation in Smart Grid. IEEE Trans. Ind. Informatics 14 (8) (2018)
Benjamin Fish, Lev Reyzin, Benjamin I. P. Rubinstein
Sublinear-Time Adaptive Data Analysis. ISAIM (2018)
Maryam Fanaeepour, Benjamin I. P. Rubinstein
Histogramming Privately Ever After: Differentially-Private Data-Dependent Error Bound Optimisation. ICDE (2018)
Chris Culnane, Benjamin I. P. Rubinstein, Vanessa Teague
Health Data in an Open World. CoRR (2017)
Chris Culnane, Benjamin I. P. Rubinstein, Vanessa Teague
Privacy Assessment of De-identified Opal Data: A report for Transport for NSW. CoRR (2017)
Benjamin I. P. Rubinstein, Francesco Aldà
Pain-Free Random Differential Privacy with Sensitivity Sampling. CoRR (2017)

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Publication Activity (10 Years)

Top Topics

Top Venues

Benjamin I. P. Rubinstein