Benjamin I. P. Rubinstein

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Anthony D. JosephUniversity of California BerkeleyVerified email at eecs.berkeley.edu
Ling HuangAHI FintechVerified email at cs.berkeley.edu
Peter BartlettProfessor, EECS and Statistics, UC BerkeleyVerified email at cs.berkeley.edu
Nina TaftSenior Research Scientist, GoogleVerified email at google.com
Christos DimitrakakisProfessor, University of OsloVerified email at a3.epfl.ch
Satish B RaoVerified email at berkeley.edu
James BaileyProfessor, School of Computing and Information Systems, University of MelbourneVerified email at unimelb.edu.au
Aikaterini (Katerina) MitrokotsaProfessor, Chalmers University of TechnologyVerified email at chalmers.se
Joachim Hyam RubinsteinMelbourne UniversityVerified email at unimelb.edu.au
Jiazhen HeAstraZenecaVerified email at astrazeneca.com
Vanessa TeagueThinking Cybersecurity and The Australian National UniversityVerified email at anu.edu.au
Tansu AlpcanProfessor, Dept. of EEE, the University of MelbourneVerified email at unimelb.edu.au
Christopher LeckieProfessor, Computing and Information Systems, The University of MelbourneVerified email at unimelb.edu.au
Yi HanResearch Fellow, Computing and Information Systems, University of MelbourneVerified email at unimelb.edu.au
Zuhe ZhangSchool of Computing & Information Systems, The University of MelbourneVerified email at unimelb.edu.au
Chris CulnaneUniversity of Melbourne (School of Computing and Information Systems)Verified email at unimelb.edu.au
Trevor CohnSchool of Computing and Information Systems, University of MelbourneVerified email at unimelb.edu.au
Bo ZhaoPinterestVerified email at pinterest.com
Jiawei HanAbel Bliss Professor of Computer Science, University of IllinoisVerified email at cs.uiuc.edu
Dawn SongProfessor of Computer Science, UC BerkeleyVerified email at cs.berkeley.edu

Benjamin I. P. Rubinstein

Professor, School of Computing and Information Systems, The University of Melbourne

Verified email at unimelb.edu.au - Homepage

Machine Learning Artificial Intelligence Differential Privacy Adversarial Machine Learning Record Linkage


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Adversarial machine learning L Huang, AD Joseph, B Nelson, BIP Rubinstein, JD Tygar Proceedings of the 4th ACM Workshop on Security and Artificial Intelligence …, 2011	932	2011
A Bayesian approach to discovering truth from conflicting sources for data integration B Zhao, BIP Rubinstein, J Gemmell, J Han Proceedings of the VLDB Endowment 5 (6), 550-561, 2012	380	2012
ANTIDOTE: Understanding and defending against poisoning of anomaly detectors BIP Rubinstein, B Nelson, L Huang, AD Joseph, S Lau, S Rao, N Taft, ... Proceedings of the 9th ACM SIGCOMM Conference on Internet Measurement …, 2009	324	2009
Exploiting Machine Learning to Subvert Your Spam Filter. B Nelson, M Barreno, FJ Chi, AD Joseph, BIP Rubinstein, U Saini, ... First USENIX Workshop on Large-scale Exploits and Emergent Threats (LEET'08 …, 2008	282	2008
Learning in a large function space: Privacy-preserving mechanisms for SVM learning BIP Rubinstein, PL Bartlett, L Huang, N Taft Journal of Privacy and Confidentiality 4 (1), 65-100, 2012	244	2012
Link prediction by de-anonymization: How we won the kaggle social network challenge A Narayanan, E Shi, BIP Rubinstein The 2011 International Joint Conference on Neural Networks (IJCNN), 1825-1834, 2011	200	2011
Identifying At-Risk Students in Massive Open Online Courses J He, J Bailey, BIP Rubinstein, R Zhang Proceedings of the 29th AAAI Conference on Artificial Intelligence (AAAI …, 2015	163	2015
PPFA: Privacy preserving fog-enabled aggregation in smart grid L Lyu, K Nandakumar, B Rubinstein, J Jin, J Bedo, M Palaniswami IEEE Transactions on Industrial Informatics 14 (8), 3733-3744, 2018	119	2018
Query Strategies for Evading Convex-Inducing Classifiers. B Nelson, BIP Rubinstein, L Huang, AD Joseph, SJ Lee, S Rao, JD Tygar Journal of Machine Learning Research 13 (5), 2012	107	2012
Misleading learners: Co-opting your spam filter B Nelson, M Barreno, FJ Chi, AD Joseph, BIP Rubinstein, U Saini, ... Machine Learning in Cyber Trust, 17-51, 2009	101	2009
Security evaluation of support vector machines in adversarial environments B Biggio, I Corona, B Nelson, BIP Rubinstein, D Maiorca, G Fumera, ... Support Vector Machines Applications, 105-153, 2014	95	2014
Adaptive bidding for display advertising A Ghosh, BIP Rubinstein, S Vassilvitskii, M Zinkevich Proceedings of the 18th International Conference on World Wide Web, 251-260, 2009	91	2009
Robust and private Bayesian inference C Dimitrakakis, B Nelson, A Mitrokotsa, BIP Rubinstein International Conference on Algorithmic Learning Theory, 291-305, 2014	90	2014
Evolving quantum circuits using genetic programming BIP Rubinstein Proceedings of the 2001 Congress on Evolutionary Computation, 144-151, 2001	81	2001
A game theoretical approach to defend against co-resident attacks in cloud computing: Preventing co-residence using semi-supervised learning Y Han, T Alpcan, J Chan, C Leckie, BIP Rubinstein IEEE Transactions on information Forensics and Security 11 (3), 556-570, 2015	71	2015
On the differential privacy of Bayesian inference Z Zhang, B Rubinstein, C Dimitrakakis Proceedings of the 30th AAAI Conference on Artificial Intelligence (AAAI …, 2016	69	2016
Machine-learning algorithms predict graft failure after liver transplantation L Lau, Y Kankanige, B Rubinstein, R Jones, C Christophi, V Muralidharan, ... Transplantation 101 (4), e125, 2017	58	2017
Stealthy poisoning attacks on PCA-based anomaly detectors BIP Rubinstein, B Nelson, L Huang, AD Joseph, S Lau, S Rao, N Taft, ... ACM SIGMETRICS Performance Evaluation Review 37 (2), 73-74, 2009	57	2009
Near-Optimal Evasion of Convex-Inducing Classifiers. B Nelson, BIP Rubinstein, L Huang, AD Joseph, S Lau, SJ Lee, S Rao, ... Proceedings of the Thirteenth International Conference on Artificial …, 2010	54	2010
Open problems in the security of learning M Barreno, PL Bartlett, FJ Chi, AD Joseph, B Nelson, BIP Rubinstein, ... Proceedings of the 1st ACM Workshop on Artificial Intelligence & Security …, 2008	52	2008

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