stochastic optimization

KrADagrad: Kronecker approximation-domination gradient preconditioned stochastic optimization UAI 2023 Learning Unnormalized Statistical Models via Compositional Optimization ICML 2023 Mean Payoff Optimization for Systems of Periodic Service and Maintenance IJCAI 2023 Memory-Based Optimization Methods for Model-Agnostic Meta-Learning and Personalized Federated Learning JMLR 2023 Minimax AUC Fairness: Efficient Algorithm with Provable Convergence AAAI 2023 Mobilizing Personalized Federated Learning in Infrastructure-Less and Heterogeneous Environments via Random Walk Stochastic ADMM NeurIPS 2023 Momentum Provably Improves Error Feedback! NeurIPS 2023 Nash Regret Guarantees for Linear Bandits NeurIPS 2023 Non-Convex Bilevel Optimization with Time-Varying Objective Functions NeurIPS 2023 Non-Smooth Weakly-Convex Finite-sum Coupled Compositional Optimization NeurIPS 2023 No-Regret Online Reinforcement Learning with Adversarial Losses and Transitions NeurIPS 2023 Online Saddle Point Tracking with Decision-Dependent Data L4DC 2023 On the Convergence of AdaGrad(Norm) on R^d: Beyond Convexity, Non-Asymptotic Rate and Acceleration ICLR 2023 On the Convergence of Distributed Stochastic Bilevel Optimization Algorithms over a Network AISTATS 2023 On the Convergence of Stochastic Gradient Descent with Bandwidth-based Step Size JMLR 2023 Optimal Extragradient-Based Algorithms for Stochastic Variational Inequalities with Separable Structure NeurIPS 2023 Optimal Online Generalized Linear Regression with Stochastic Noise and Its Application to Heteroscedastic Bandits ICML 2023 Optimal Stochastic Non-smooth Non-convex Optimization through Online-to-Non-convex Conversion ICML 2023 Optimistic Online Mirror Descent for Bridging Stochastic and Adversarial Online Convex Optimization ICML 2023 Orthogonal Directions Constrained Gradient Method: from non-linear equality constraints to Stiefel manifold COLT 2023 Predictor-corrector algorithms for stochastic optimization under gradual distribution shift ICLR 2023 Private Federated Frequency Estimation: Adapting to the Hardness of the Instance NeurIPS 2023 Private Stochastic Optimization with Large Worst-Case Lipschitz Parameter: Optimal Rates for (Non-Smooth) Convex Losses and Extension to Non-Convex Losses ALT 2023 Probably Anytime-Safe Stochastic Combinatorial Semi-Bandits ICML 2023 Prometheus: Taming Sample and Communication Complexities in Constrained Decentralized Stochastic Bilevel Learning ICML 2023