Benjamin I. P. Rubinstein

According to our database1, Benjamin I. P. Rubinstein
  • authored at least 68 papers between 2003 and 2017.
  • has a "Dijkstra number"2 of four.

Timeline

Legend:

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In proceedings 
Article 
PhD thesis 
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Homepages:

On csauthors.net:

Bibliography

2017
In Search of an Entity Resolution OASIS: Optimal Asymptotic Sequential Importance Sampling.
PVLDB, 2017

Differential Privacy for Bayesian Inference through Posterior Sampling.
Journal of Machine Learning Research, 2017

Sublinear-Time Adaptive Data Analysis.
CoRR, 2017

Pain-Free Random Differential Privacy with Sensitivity Sampling.
CoRR, 2017

In Search of an Entity Resolution OASIS: Optimal Asymptotic Sequential Importance Sampling.
CoRR, 2017

Adequacy of the Gradient-Descent Method for Classifier Evasion Attacks.
CoRR, 2017

End-to-End Differentially-Private Parameter Tuning in Spatial Histograms.
CoRR, 2017

Privacy Assessment of De-identified Opal Data: A report for Transport for NSW.
CoRR, 2017

Pain-Free Random Differential Privacy with Sensitivity Sampling.
Proceedings of the 34th International Conference on Machine Learning, 2017

The Bernstein Mechanism: Function Release under Differential Privacy.
Proceedings of the Thirty-First AAAI Conference on Artificial Intelligence, 2017

2016
A Game Theoretical Approach to Defend Against Co-Resident Attacks in Cloud Computing: Preventing Co-Residence Using Semi-Supervised Learning.
IEEE Trans. Information Forensics and Security, 2016

TopicResponse: A Marriage of Topic Modelling and Rasch Modelling for Automatic Measurement in MOOCs.
CoRR, 2016

Beyond Points and Paths: Counting Private Bodies.
CoRR, 2016

Large-Scale Strategic Games and Adversarial Machine Learning.
CoRR, 2016

Validity: a framework for cross-disciplinary collaboration in mining indicators of learning from MOOC forums.
Proceedings of the Sixth International Conference on Learning Analytics & Knowledge, 2016

Fast trajectory clustering using Hashing methods.
Proceedings of the 2016 International Joint Conference on Neural Networks, 2016

Large Scale Metric learning.
Proceedings of the 2016 International Joint Conference on Neural Networks, 2016

Beyond Points and Paths: Counting Private Bodies.
Proceedings of the IEEE 16th International Conference on Data Mining, 2016

Large-scale strategic games and adversarial machine learning.
Proceedings of the 55th IEEE Conference on Decision and Control, 2016

On the Differential Privacy of Bayesian Inference.
Proceedings of the Thirtieth AAAI Conference on Artificial Intelligence, 2016

MOOCs Meet Measurement Theory: A Topic-Modelling Approach.
Proceedings of the Thirtieth AAAI Conference on Artificial Intelligence, 2016

2015
Principled Graph Matching Algorithms for Integrating Multiple Data Sources.
IEEE Trans. Knowl. Data Eng., 2015

The CASE histogram: privacy-aware processing of trajectory data using aggregates.
GeoInformatica, 2015

On the Differential Privacy of Bayesian Inference.
CoRR, 2015

MOOCs Meet Measurement Theory: A Topic-Modelling Approach.
CoRR, 2015

Sub-Merge: Diving Down to the Attribute-Value Level in Statistical Schema Matching.
Proceedings of the Twenty-Ninth AAAI Conference on Artificial Intelligence, 2015

Identifying At-Risk Students in Massive Open Online Courses.
Proceedings of the Twenty-Ninth AAAI Conference on Artificial Intelligence, 2015

2014
Principled Graph Matching Algorithms for Integrating Multiple Data Sources.
CoRR, 2014

Bounding Embeddings of VC Classes into Maximum Classes.
CoRR, 2014

Security Evaluation of Support Vector Machines in Adversarial Environments.
CoRR, 2014

Workshop Summary of AISec'14: 2014 Workshop on Artificial Intelligent and Security.
Proceedings of the 2014 ACM SIGSAC Conference on Computer and Communications Security, 2014

Robust and Private Bayesian Inference.
Proceedings of the Algorithmic Learning Theory - 25th International Conference, 2014

2013
Robust, Secure and Private Bayesian Inference.
CoRR, 2013

On the challenges of balancing privacy and utility of open health data.
Proceedings of the Joint Proceedings of the Workshop on AI Problems and Approaches for Intelligent Environments and Workshop on Semantic Cities, 2013

2012
On the Stability of Empirical Risk Minimization in the Presence of Multiple Risk Minimizers.
IEEE Trans. Information Theory, 2012

A Learning-Based Approach to Reactive Security.
IEEE Trans. Dependable Sec. Comput., 2012

A Bayesian Approach to Discovering Truth from Conflicting Sources for Data Integration.
PVLDB, 2012

A Geometric Approach to Sample Compression.
Journal of Machine Learning Research, 2012

Query Strategies for Evading Convex-Inducing Classifiers.
Journal of Machine Learning Research, 2012

Scaling Multiple-Source Entity Resolution using Statistically Efficient Transfer Learning
CoRR, 2012

A Bayesian Approach to Discovering Truth from Conflicting Sources for Data Integration
CoRR, 2012

Scaling multiple-source entity resolution using statistically efficient transfer learning.
Proceedings of the 21st ACM International Conference on Information and Knowledge Management, 2012

Fifth ACM workshop on artificial intelligence and security (AISec 2012).
Proceedings of the ACM Conference on Computer and Communications Security, 2012

2011
How Open Should Open Source Be?
CoRR, 2011

Improving Entity Resolution with Global Constraints
CoRR, 2011

Link Prediction by De-anonymization: How We Won the Kaggle Social Network Challenge
CoRR, 2011

Link prediction by de-anonymization: How We Won the Kaggle Social Network Challenge.
Proceedings of the 2011 International Joint Conference on Neural Networks, 2011

Adversarial machine learning.
Proceedings of the 4th ACM Workshop on Security and Artificial Intelligence, 2011

2010
Near-Optimal Evasion of Convex-Inducing Classifiers.
Proceedings of the Thirteenth International Conference on Artificial Intelligence and Statistics, 2010

Corrigendum to "Shifting: One-inclusion mistake bounds and sample compression" [J. Comput. System Sci 75 (1) (2009) 37-59].
J. Comput. Syst. Sci., 2010

Query Strategies for Evading Convex-Inducing Classifiers
CoRR, 2010

Near-Optimal Evasion of Convex-Inducing Classifiers
CoRR, 2010

On the Stability of Empirical Risk Minimization in the Presence of Multiple Risk Minimizers
CoRR, 2010

Classifier Evasion: Models and Open Problems.
Proceedings of the Privacy and Security Issues in Data Mining and Machine Learning, 2010

A Learning-Based Approach to Reactive Security.
Proceedings of the Financial Cryptography and Data Security, 14th International Conference, 2010

2009
Stealthy poisoning attacks on PCA-based anomaly detectors.
SIGMETRICS Performance Evaluation Review, 2009

Shifting: One-inclusion mistake bounds and sample compression.
J. Comput. Syst. Sci., 2009

A Learning-Based Approach to Reactive Security
CoRR, 2009

Learning in a Large Function Space: Privacy-Preserving Mechanisms for SVM Learning
CoRR, 2009

A Geometric Approach to Sample Compression
CoRR, 2009

Adaptive bidding for display advertising.
Proceedings of the 18th International Conference on World Wide Web, 2009

ANTIDOTE: understanding and defending against poisoning of anomaly detectors.
Proceedings of the 9th ACM SIGCOMM Internet Measurement Conference, IMC 2009, Chicago, 2009

2008
Evading Anomaly Detection through Variance Injection Attacks on PCA.
Proceedings of the Recent Advances in Intrusion Detection, 11th International Symposium, 2008

Exploiting Machine Learning to Subvert Your Spam Filter.
Proceedings of the First USENIX Workshop on Large-Scale Exploits and Emergent Threats, 2008

Geometric & Topological Representations of Maximum Classes with Applications to Sample Compression.
Proceedings of the 21st Annual Conference on Learning Theory, 2008

Open problems in the security of learning.
Proceedings of the 1st ACM Workshop on Security and Artificial Intelligence, 2008

2006
Shifting, One-Inclusion Mistake Bounds and Tight Multiclass Expected Risk Bounds.
Proceedings of the Advances in Neural Information Processing Systems 19, 2006

2003
Machine learning in low-level microarray analysis.
SIGKDD Explorations, 2003


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