 |
 Operationalizing the Legal Principle of Data Minimization for
PersonalizationAnnual International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR), 2020 |
 To Split or Not to Split: The Impact of Disparate Treatment in
ClassificationIEEE Transactions on Information Theory (IEEE Trans. Inf. Theory), 2020 |
 Adversarial Learning of Privacy-Preserving and Task-Oriented
RepresentationsAAAI Conference on Artificial Intelligence (AAAI), 2019 |
 Privacy and Utility Preserving Sensor-Data TransformationsPervasive and Mobile Computing (PMC), 2019 |
 Developing Non-Stochastic Privacy-Preserving Policies Using
Agglomerative ClusteringIEEE Transactions on Information Forensics and Security (IEEE TIFS), 2019 |
 Noiseless PrivacyIEEE Transactions on Big Data (IEEE Trans. Big Data), 2019 |
 Obfuscation via Information Density EstimationInternational Conference on Artificial Intelligence and Statistics (AISTATS), 2019 |
 SoK: Differential PrivaciesProceedings on Privacy Enhancing Technologies (PoPETs), 2019 |
 Privacy Against Brute-Force Inference AttacksInternational Symposium on Information Theory (ISIT), 2019 |
 Privacy-Preserving Adversarial NetworksAllerton Conference on Communication, Control, and Computing (Allerton), 2017 |
 Minimax Filter: Learning to Preserve Privacy from Inference AttacksJournal of machine learning research (JMLR), 2016 |
 Privacy-Enhanced Architecture for Occupancy-based HVAC ControlInternational Conference on Cyber-Physical Systems (ICCPS), 2016 |
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 Managing your Private and Public Data: Bringing down Inference Attacks
against your PrivacyIEEE Journal on Selected Topics in Signal Processing (JSTSP), 2014 |
 Privacy Tradeoffs in Predictive AnalyticsMeasurement and Modeling of Computer Systems (SIGMETRICS), 2014 |
 Recommending with an Agenda: Active Learning of Private Attributes using
Matrix FactorizationACM Conference on Recommender Systems (RecSys), 2013 |
