Privacy

Adaptive Learning with Robust Generalization Guarantees COLT 2016 Alpenhorn: Bootstrapping Secure Communication without Leaking Metadata OSDI 2016 Big Data Analytics over Encrypted Datasets with Seabed OSDI 2016 Bootstrap Model Aggregation for Distributed Statistical Learning NeurIPS 2016 CryptoNets: Applying Neural Networks to Encrypted Data with High Throughput and Accuracy ICML 2016 Differentially Private Chi-Squared Hypothesis Testing: Goodness of Fit and Independence Testing ICML 2016 Differentially Private Data Releasing for Smooth Queries JMLR 2016 Differentially Private Policy Evaluation ICML 2016 Differential Privacy without Sensitivity NeurIPS 2016 Discrete Distribution Estimation under Local Privacy ICML 2016 Efficient Private Empirical Risk Minimization for High-dimensional Learning ICML 2016 Extremal Mechanisms for Local Differential Privacy JMLR 2016 Fast Distributed Submodular Cover: Public-Private Data Summarization NeurIPS 2016 Learning privately from multiparty data ICML 2016 Learning with Differential Privacy: Stability, Learnability and the Sufficiency and Necessity of ERM Principle JMLR 2016 Metadata-conscious anonymous messaging ICML 2016 On Regularizing Rademacher Observation Losses NeurIPS 2016 Privacy Odometers and Filters: Pay-as-you-Go Composition NeurIPS 2016 Privacy-Preserving Speech Analytics for Automatic Assessment of Student Collaboration Interspeech 2016 Private Causal Inference AISTATS 2016 Secure Approximation Guarantee for Cryptographically Private Empirical Risk Minimization ACML 2016 Shuffler: Fast and Deployable Continuous Code Re-Randomization OSDI 2016 Unobservable Communication over Fully Untrusted Infrastructure OSDI 2016 A Market Framework for Eliciting Private Data NeurIPS 2015 Differentially Private Bayesian Optimization ICML 2015