Probability

Open Problem: Tight Characterization of Instance-Optimal Identity Testing COLT 2024 Optimal Algorithms for Augmented Testing of Discrete Distributions NeurIPS 2024 Optimal Differentially Private Model Training with Public Data ICML 2024 Optimal Scaling for the Proximal Langevin Algorithm in High Dimensions JMLR 2024 Optimal Transport with Tempered Exponential Measures AAAI 2024 Parameter Symmetry and Noise Equilibrium of Stochastic Gradient Descent NeurIPS 2024 Pareto Smoothed Importance Sampling JMLR 2024 Path-Guided Particle-based Sampling ICML 2024 PGMax: Factor Graphs for Discrete Probabilistic Graphical Models and Loopy Belief Propagation in JAX JMLR 2024 Posterior Sampling-Based Bayesian Optimization with Tighter Bayesian Regret Bounds ICML 2024 Pricing with Contextual Elasticity and Heteroscedastic Valuation ICML 2024 Principled Preferential Bayesian Optimization ICML 2024 PrIsing: Privacy-Preserving Peer Effect Estimation via Ising Model AISTATS 2024 Probabilities of Causation with Nonbinary Treatment and Effect AAAI 2024 Probability Distribution of Hypervolume Improvement in Bi-objective Bayesian Optimization ICML 2024 Profile Reconstruction from Private Sketches ICML 2024 Provable Advantage in Quantum PAC Learning COLT 2024 Proving Linear Mode Connectivity of Neural Networks via Optimal Transport AISTATS 2024 Pure Differential Privacy for Functional Summaries with a Laplace-like Process JMLR 2024 Quadratic Quantum Variational Monte Carlo NeurIPS 2024 Quantum Algorithms for Non-smooth Non-convex Optimization NeurIPS 2024 Repelling Random Walks ICLR 2024 Risk Estimation in a Markov Cost Process: Lower and Upper Bounds ICML 2024 Robust Graph Matching when Nodes are Corrupt ICML 2024 Robustly Learning Single-Index Models via Alignment Sharpness ICML 2024