stochastic optimization

Proportional Response: Contextual Bandits for Simple and Cumulative Regret Minimization NeurIPS 2023 PROTES: Probabilistic Optimization with Tensor Sampling NeurIPS 2023 Provable convergence guarantees for black-box variational inference NeurIPS 2023 Provable Multi-instance Deep AUC Maximization with Stochastic Pooling ICML 2023 Proximal Stochastic Recursive Momentum Methods for Nonconvex Composite Decentralized Optimization AAAI 2023 Quantum speedups for stochastic optimization NeurIPS 2023 Randomized Greedy Learning for Non-monotone Stochastic Submodular Maximization Under Full-bandit Feedback AISTATS 2023 Reinforcement Learning with General Utilities: Simpler Variance Reduction and Large State-Action Space ICML 2023 Revisiting Gradient Clipping: Stochastic bias and tight convergence guarantees ICML 2023 Revisiting Sampling for Combinatorial Optimization ICML 2023 Revisiting Simple Regret: Fast Rates for Returning a Good Arm ICML 2023 Sample Complexity for Quadratic Bandits: Hessian Dependent Bounds and Optimal Algorithms NeurIPS 2023 Single-Call Stochastic Extragradient Methods for Structured Non-monotone Variational Inequalities: Improved Analysis under Weaker Conditions NeurIPS 2023 Stability and Generalization of Stochastic Optimization with Nonconvex and Nonsmooth Problems COLT 2023 Stochastic Approximation Approaches to Group Distributionally Robust Optimization NeurIPS 2023 Stochastic Differentially Private and Fair Learning ICLR 2023 Stochastic Methods for AUC Optimization subject to AUC-based Fairness Constraints AISTATS 2023 Stochastic Mirror Descent for Large-Scale Sparse Recovery AISTATS 2023 Stochastic Optimization for Spectral Risk Measures AISTATS 2023 Stochastic Optimization under Distributional Drift JMLR 2023 Stochastic Policy Gradient Methods: Improved Sample Complexity for Fisher-non-degenerate Policies ICML 2023 Streaming Submodular Maximization with Differential Privacy ICML 2023 Target-based Surrogates for Stochastic Optimization ICML 2023 The Acquisition of Physical Knowledge in Generative Neural Networks ICML 2023 TiAda: A Time-scale Adaptive Algorithm for Nonconvex Minimax Optimization ICLR 2023