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Benjamin I. P. Rubinstein
Person information
- affiliation: University of Melbourne, School of Computing and Information Systems, Australia
- affiliation (former): Microsoft Research
- affiliation (PhD 2010): University of California Berkeley, CA, USA
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2020 – today
- 2024
- [j26]Xuanli He, Qiongkai Xu, Jun Wang, Benjamin I. P. Rubinstein, Trevor Cohn:
SEEP: Training Dynamics Grounds Latent Representation Search for Mitigating Backdoor Poisoning Attacks. Trans. Assoc. Comput. Linguistics 12: 996-1010 (2024) - [j25]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: 163-177 (2024) - [c81]Jiankai Jin
, Olga Ohrimenko
, Benjamin I. P. Rubinstein
:
Getting a-Round Guarantees: Floating-Point Attacks on Certified Robustness. AISec@CCS 2024: 53-64 - [c80]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
:
Designing an Adaptive AI System for Operation on Board the SpIRIT Nano-Satellite. AI (1) 2024: 329-341 - [c79]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. CCS 2024: 1909-1923 - [c78]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. CVPR Workshops 2024: 6789-6798 - [c77]Zhuoqun Huang, Neil G. Marchant, Olga Ohrimenko, Benjamin I. P. Rubinstein:
CERT-ED: Certifiably Robust Text Classification for Edit Distance. EMNLP (Findings) 2024: 10813-10835 - [c76]Andrew C. Cullen, Shijie Liu, Paul Montague, Sarah Monazam Erfani, Benjamin I. P. Rubinstein:
Et Tu Certifications: Robustness Certificates Yield Better Adversarial Examples. ICML 2024 - [c75]Jun Wang, Qiongkai Xu
, Xuanli He, Benjamin I. P. Rubinstein, Trevor Cohn:
Backdoor Attacks on Multilingual Machine Translation. NAACL-HLT 2024: 4515-4534 - [c74]Andrew C. Cullen, Paul Montague, Shijie Liu, Sarah M. Erfani, Benjamin I. P. Rubinstein:
It's Simplex! Disaggregating Measures to Improve Certified Robustness. SP 2024: 2886-2900 - [i73]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 abs/2401.17628 (2024) - [i72]Jun Wang, Qiongkai Xu
, Xuanli He, Benjamin I. P. Rubinstein
, Trevor Cohn:
Backdoor Attack on Multilingual Machine Translation. CoRR abs/2404.02393 (2024) - [i71]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 abs/2404.08399 (2024) - [i70]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 abs/2404.19597 (2024) - [i69]Aref Miri Rekavandi, Olga Ohrimenko, Benjamin I. P. Rubinstein
:
RS-Reg: Probabilistic and Robust Certified Regression Through Randomized Smoothing. CoRR abs/2405.08892 (2024) - [i68]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 abs/2405.11575 (2024) - [i67]Neil G. Marchant, Benjamin I. P. Rubinstein
:
Adaptive Data Analysis for Growing Data. CoRR abs/2405.13375 (2024) - [i66]Zhuoqun Huang, Neil G. Marchant, Olga Ohrimenko, Benjamin I. P. Rubinstein
:
CERT-ED: Certifiably Robust Text Classification for Edit Distance. CoRR abs/2408.00728 (2024) - 2023
- [j24]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): 10921-10959 (2023) - [j23]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): 3533-3565 (2023) - [j22]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): 12855-12872 (2023) - [c73]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: 8861-8869 - [c72]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: 2508-2510 - [c71]Xuanli He, Qiongkai Xu
, Jun Wang, Benjamin I. P. Rubinstein, Trevor Cohn:
Mitigating Backdoor Poisoning Attacks through the Lens of Spurious Correlation. EMNLP 2023: 953-967 - [c70]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: 47-55 - [c69]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: 60-66 - [c68]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 - [i65]Neil G. Marchant, Benjamin I. P. Rubinstein
, Rebecca C. Steorts:
Bayesian Graphical Entity Resolution Using Exchangeable Random Partition Priors. CoRR abs/2301.02962 (2023) - [i64]Zhuoqun Huang, Neil G. Marchant, Keane Lucas, Lujo Bauer
, Olga Ohrimenko, Benjamin I. P. Rubinstein
:
Certified Robustness of Learning-based Static Malware Detectors. CoRR abs/2302.01757 (2023) - [i63]Andrew C. Cullen, Paul Montague, Shijie Liu, Sarah M. Erfani, Benjamin I. P. Rubinstein
:
Exploiting Certified Defences to Attack Randomised Smoothing. CoRR abs/2302.04379 (2023) - [i62]Xuanli He, Qiongkai Xu
, Jun Wang, Benjamin I. P. Rubinstein
, Trevor Cohn:
Mitigating Backdoor Poisoning Attacks through the Lens of Spurious Correlation. CoRR abs/2305.11596 (2023) - [i61]Xuanli He, Jun Wang, Benjamin I. P. Rubinstein, Trevor Cohn:
IMBERT: Making BERT Immune to Insertion-based Backdoor Attacks. CoRR abs/2305.16503 (2023) - [i60]Shijie Liu, Andrew C. Cullen, Paul Montague, Sarah M. Erfani, Benjamin I. P. Rubinstein
:
Enhancing the Antidote: Improved Pointwise Certifications against Poisoning Attacks. CoRR abs/2308.07553 (2023) - [i59]Andrew C. Cullen, Paul Montague, Shijie Liu, Sarah M. Erfani, Benjamin I. P. Rubinstein
:
It's Simplex! Disaggregating Measures to Improve Certified Robustness. CoRR abs/2309.11005 (2023) - 2022
- [j21]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): 216-229 (2022) - [j20]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): 538-548 (2022) - [c67]Neil G. Marchant
, Benjamin I. P. Rubinstein, Scott Alfeld:
Hard to Forget: Poisoning Attacks on Certified Machine Unlearning. AAAI 2022: 7691-7700 - [c66]Jun Wang, Benjamin I. P. Rubinstein, Trevor Cohn:
Measuring and Mitigating Name Biases in Neural Machine Translation. ACL (1) 2022: 2576-2590 - [c65]Sandamal Weerasinghe, Tamas Abraham, Tansu Alpcan, Sarah M. Erfani, Christopher Leckie, Benjamin I. P. Rubinstein
:
Local Intrinsic Dimensionality Signals Adversarial Perturbations. CDC 2022: 6118-6125 - [c64]Jun Wang, Xuanli He, Benjamin I. P. Rubinstein, Trevor Cohn:
Foiling Training-Time Attacks on Neural Machine Translation Systems. EMNLP (Findings) 2022: 5906-5913 - [c63]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 - [c62]Joachim Hyam Rubinstein, Benjamin I. P. Rubinstein:
Unlabelled Sample Compression Schemes for Intersection-Closed Classes and Extremal Classes. NeurIPS 2022 - [c61]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: 269-285 - [c60]Jiankai Jin, Eleanor McMurtry, Benjamin I. P. Rubinstein
, Olga Ohrimenko
:
Are We There Yet? Timing and Floating-Point Attacks on Differential Privacy Systems. SP 2022: 473-488 - [c59]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: 720-730 - [i58]Jiankai Jin, Olga Ohrimenko
, Benjamin I. P. Rubinstein
:
Getting a-Round Guarantees: Floating-Point Attacks on Certified Robustness. CoRR abs/2205.10159 (2022) - [i57]Matthias Bachfischer, Renata Borovica-Gajic
, Benjamin I. P. Rubinstein
:
Testing the Robustness of Learned Index Structures. CoRR abs/2207.11575 (2022) - [i56]J. Hyam Rubinstein, Benjamin I. P. Rubinstein
:
Unlabelled Sample Compression Schemes for Intersection-Closed Classes and Extremal Classes. CoRR abs/2210.05455 (2022) - [i55]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 abs/2210.06077 (2022) - 2021
- [j19]Song Wang
, Juan Fernando Balarezo
, Sithamparanathan Kandeepan
, Akram Al-Hourani
, Karina Gomez Chavez, Benjamin I. P. Rubinstein
:
Machine Learning in Network Anomaly Detection: A Survey. IEEE Access 9: 152379-152396 (2021) - [j18]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): 406-421 (2021) - [c58]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: 11682-11690 - [c57]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: 1463-1473 - [c56]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: 4711-4717 - [c55]Guoxin Sun, Tansu Alpcan, Benjamin I. P. Rubinstein
, Seyit Camtepe
:
A Communication Security Game on Switched Systems for Autonomous Vehicle Platoons. CDC 2021: 2690-2695 - [c54]Chang Xu, Jun Wang, Francisco Guzmán, Benjamin I. P. Rubinstein, Trevor Cohn:
Mitigating Data Poisoning in Text Classification with Differential Privacy. EMNLP (Findings) 2021: 4348-4356 - [c53]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: 600-611 - [c52]Bastian Oetomo, R. Malinga Perera, Renata Borovica-Gajic
, Benjamin I. P. Rubinstein
:
Cutting to the Chase with Warm-Start Contextual Bandits. ICDM 2021: 459-468 - [c51]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: 3176-3184 - [c50]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: 1337-1341 - [c49]Neil G. Marchant
, Benjamin I. P. Rubinstein
:
Needle in a Haystack: Label-Efficient Evaluation under Extreme Class Imbalance. KDD 2021: 1180-1190 - [c48]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: 17642-17655 - [c47]Guoxin Sun, Tansu Alpcan, Benjamin I. P. Rubinstein
, Seyit Camtepe
:
Strategic Mitigation Against Wireless Attacks on Autonomous Platoons. ECML/PKDD (4) 2021: 69-84 - [c46]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: 3638-3650 - [i54]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 abs/2104.00671 (2021) - [i53]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 abs/2107.05243 (2021) - [i52]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 abs/2107.08357 (2021) - [i51]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 abs/2108.10130 (2021) - [i50]Neil G. Marchant, Benjamin I. P. Rubinstein, Scott Alfeld:
Hard to Forget: Poisoning Attacks on Certified Machine Unlearning. CoRR abs/2109.08266 (2021) - [i49]Sandamal Weerasinghe, Tansu Alpcan, Sarah M. Erfani, Christopher Leckie, Benjamin I. P. Rubinstein:
Local Intrinsic Dimensionality Signals Adversarial Perturbations. CoRR abs/2109.11803 (2021) - [i48]Guoxin Sun, Tansu Alpcan, Benjamin I. P. Rubinstein, Seyit Camtepe:
A Communication Security Game on Switched Systems for Autonomous Vehicle Platoons. CoRR abs/2109.14208 (2021) - [i47]Jiankai Jin, Eleanor McMurtry, Benjamin I. P. Rubinstein, Olga Ohrimenko:
Are We There Yet? Timing and Floating-Point Attacks on Differential Privacy Systems. CoRR abs/2112.05307 (2021) - [i46]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 abs/2112.15498 (2021) - 2020
- [c45]Naufal Fikri Setiawan, Benjamin I. P. Rubinstein
, Renata Borovica-Gajic
:
Function Interpolation for Learned Index Structures. ADC 2020: 68-80 - [c44]Benjamin Fish, Lev Reyzin, Benjamin I. P. Rubinstein:
Sampling Without Compromising Accuracy in Adaptive Data Analysis. ALT 2020: 297-318 - [c43]Dongge Liu
, Gidon Ernst
, Toby Murray, Benjamin I. P. Rubinstein
:
Legion: Best-First Concolic Testing (Competition Contribution). FASE 2020: 545-549 - [c42]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: 1-8 - [c41]Dongge Liu
, Gidon Ernst
, Toby Murray, Benjamin I. P. Rubinstein
:
LEGION: Best-First Concolic Testing. ASE 2020: 54-65 - [c40]Leyla Roohi
, Benjamin I. P. Rubinstein
, Vanessa Teague
:
Assessing Centrality Without Knowing Connections. PAKDD (2) 2020: 152-163 - [i45]Dongge Liu, Gidon Ernst, Toby Murray, Benjamin I. P. Rubinstein:
Legion: Best-First Concolic Testing. CoRR abs/2002.06311 (2020) - [i44]Leyla Roohi, Benjamin I. P. Rubinstein, Vanessa Teague:
Assessing Centrality Without Knowing Connections. CoRR abs/2005.13787 (2020) - [i43]Neil G. Marchant, Benjamin I. P. Rubinstein:
A general framework for label-efficient online evaluation with asymptotic guarantees. CoRR abs/2006.06963 (2020) - [i42]Roei Gelbhart, Benjamin I. P. Rubinstein:
Discrete Few-Shot Learning for Pan Privacy. CoRR abs/2006.13120 (2020) - [i41]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 abs/2006.15417 (2020) - [i40]Tobias Edwards, Benjamin I. P. Rubinstein, Zuhe Zhang, Sanming Zhou:
A Graph Symmetrisation Bound on Channel Information Leakage under Blowfish Privacy. CoRR abs/2007.05975 (2020) - [i39]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 abs/2010.09208 (2020) - [i38]Chang Xu, Jun Wang, Yuqing Tang, Francisco Guzmán, Benjamin I. P. Rubinstein, Trevor Cohn:
Targeted Poisoning Attacks on Black-Box Neural Machine Translation. CoRR abs/2011.00675 (2020) - [i37]Chris Culnane, Benjamin I. P. Rubinstein, David Watts:
Not fit for Purpose: A critical analysis of the 'Five Safes'. CoRR abs/2011.02142 (2020)
2010 – 2019
- 2019
- [c39]Scott Alfeld, Ara Vartanian, Lucas Newman-Johnson, Benjamin I. P. Rubinstein:
Attacking Data Transforming Learners at Training Time. AAAI 2019: 3167-3174 - [c38]Yuan Li, Benjamin I. P. Rubinstein, Trevor Cohn:
Exploiting Worker Correlation for Label Aggregation in Crowdsourcing. ICML 2019: 3886-3895 - [c37]Leyla Roohi, Benjamin I. P. Rubinstein
, Vanessa Teague:
Differentially-Private Two-Party Egocentric Betweenness Centrality. INFOCOM 2019: 2233-2241 - [c36]Yuan Li, Benjamin I. P. Rubinstein
, Trevor Cohn:
Truth Inference at Scale: A Bayesian Model for Adjudicating Highly Redundant Crowd Annotations. WWW 2019: 1028-1038 - [i36]Leyla Roohi, Benjamin I. P. Rubinstein, Vanessa Teague:
Differentially-Private Two-Party Egocentric Betweenness Centrality. CoRR abs/1901.05562 (2019) - [i35]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 abs/1902.07500 (2019) - [i34]Yuan Li, Benjamin I. P. Rubinstein, Trevor Cohn:
Truth Inference at Scale: A Bayesian Model for Adjudicating Highly Redundant Crowd Annotations. CoRR abs/1902.08918 (2019) - [i33]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 abs/1902.09062 (2019) - [i32]Chris Culnane, Benjamin I. P. Rubinstein, Vanessa Teague:
Stop the Open Data Bus, We Want to Get Off. CoRR abs/1908.05004 (2019) - [i31]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 abs/1909.06039 (2019) - 2018
- [j17]Maryam Fanaeepour
, Benjamin I. P. Rubinstein
:
Differentially private counting of users' spatial regions. Knowl. Inf. Syst. 54(1): 5-32 (2018) - [j16]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): 3733-3744 (2018) - [c35]Yi Han, Benjamin I. P. Rubinstein:
Adequacy of the Gradient-Descent Method for Classifier Evasion Attacks. AAAI Workshops 2018: 237-244 - [c34]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: 145-165 - [c33]Maryam Fanaeepour
, Benjamin I. P. Rubinstein
:
Histogramming Privately Ever After: Differentially-Private Data-Dependent Error Bound Optimisation. ICDE 2018: 1204-1207 - [c32]Benjamin Fish, Lev Reyzin, Benjamin I. P. Rubinstein:
Sublinear-Time Adaptive Data Analysis. ISAIM 2018 - [c31]Zay Maung Maung Aye, Benjamin I. P. Rubinstein
, Kotagiri Ramamohanarao:
Fast Manifold Landmarking Using Locality-Sensitive Hashing. PAKDD (3) 2018: 452-464 - [i30]Chris Culnane, Benjamin I. P. Rubinstein, Vanessa Teague:
Options for encoding names for data linking at the Australian Bureau of Statistics. CoRR abs/1802.07975 (2018) - [i29]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 abs/1808.05770 (2018) - 2017
- [j15]Christos Dimitrakakis, Blaine Nelson, Zuhe Zhang, Aikaterini Mitrokotsa
, Benjamin I. P. Rubinstein:
Differential Privacy for Bayesian Inference through Posterior Sampling. J. Mach. Learn. Res. 18: 11:1-11:39 (2017) - [j14]Neil G. Marchant
, Benjamin I. P. Rubinstein
:
In Search of an Entity Resolution OASIS: Optimal Asymptotic Sequential Importance Sampling. Proc. VLDB Endow. 10(11): 1322-1333 (2017) - [c30]Francesco Aldà, Benjamin I. P. Rubinstein:
The Bernstein Mechanism: Function Release under Differential Privacy. AAAI 2017: 1705-1711 - [c29]Benjamin I. P. Rubinstein, Francesco Aldà:
Pain-Free Random Differential Privacy with Sensitivity Sampling. ICML 2017: 2950-2959 - [c28]Xunyun Liu, Aaron Harwood, Shanika Karunasekera, Benjamin I. P. Rubinstein
, Rajkumar Buyya:
E-Storm: Replication-Based State Management in Distributed Stream Processing Systems. ICPP 2017: 571-580 - [i28]Maryam Fanaeepour
, Benjamin I. P. Rubinstein:
End-to-End Differentially-Private Parameter Tuning in Spatial Histograms. CoRR abs/1702.05607 (2017) - [i27]Neil G. Marchant, Benjamin I. P. Rubinstein:
In Search of an Entity Resolution OASIS: Optimal Asymptotic Sequential Importance Sampling. CoRR abs/1703.00617 (2017) - [i26]Yi Han, Benjamin I. P. Rubinstein:
Adequacy of the Gradient-Descent Method for Classifier Evasion Attacks. CoRR abs/1704.01704 (2017) - [i25]Chris Culnane, Benjamin I. P. Rubinstein, Vanessa Teague:
Privacy Assessment of De-identified Opal Data: A report for Transport for NSW. CoRR abs/1704.08547 (2017) - [i24]Benjamin I. P. Rubinstein, Francesco Aldà:
Pain-Free Random Differential Privacy with Sensitivity Sampling. CoRR abs/1706.02562 (2017) - [i23]Benjamin Fish, Lev Reyzin, Benjamin I. P. Rubinstein:
Sublinear-Time Adaptive Data Analysis. CoRR abs/1709.09778 (2017) - [i22]Chris Culnane, Benjamin I. P. Rubinstein, 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. CoRR abs/1712.00871 (2017) - [i21]