distribution estimation

Anonymized Histograms in Intermediate Privacy Models NeurIPS 2022 Distributed NLI: Learning to Predict Human Opinion Distributions for Language Reasoning ACL 2022 Learning to Attack Federated Learning: A Model-based Reinforcement Learning Attack Framework NeurIPS 2022 Local Differential Privacy for Belief Functions AAAI 2022 On the Efficient Implementation of High Accuracy Optimality of Profile Maximum Likelihood NeurIPS 2022 Source-Free Domain Adaptation via Distribution Estimation CVPR 2022 Structural Agnostic Modeling: Adversarial Learning of Causal Graphs JMLR 2022 Adaptive Sampling for Estimating Distributions: A Bayesian Upper Confidence Bound Approach L4DC 2021 Breaking The Dimension Dependence in Sparse Distribution Estimation under Communication Constraints COLT 2021 Differentially Private Assouad, Fano, and Le Cam ALT 2021 Locally Differentially-Private Randomized Response for Discrete Distribution Learning JMLR 2021 On the High Accuracy Limitation of Adaptive Property Estimation AISTATS 2021 Pointwise Bounds for Distribution Estimation under Communication Constraints NeurIPS 2021 Robust hypothesis testing and distribution estimation in Hellinger distance AISTATS 2021 Robust Testing and Estimation under Manipulation Attacks ICML 2021 Sample Elicitation AISTATS 2021 A General Method for Robust Learning from Batches NeurIPS 2020 Bessel Smoothing and Multi-Distribution Property Estimation COLT 2020 Context Aware Local Differential Privacy ICML 2020 Instance Based Approximations to Profile Maximum Likelihood NeurIPS 2020 Learning discrete distributions with infinite support NeurIPS 2020 Locally Private Hypothesis Selection COLT 2020 Profile Entropy: A Fundamental Measure for the Learnability and Compressibility of Distributions NeurIPS 2020 SURF: A Simple, Universal, Robust, Fast Distribution Learning Algorithm NeurIPS 2020 Task Agnostic Robust Learning on Corrupt Outputs by Correlation-Guided Mixture Density Networks CVPR 2020