Yi Zhou

Revisiting Large-Scale Non-convex Distributionally Robust Optimization ICLR 2025 Large-Scale Non-convex Stochastic Constrained Distributionally Robust Optimization AAAI 2024 Non-Asymptotic Analysis for Single-Loop (Natural) Actor-Critic with Compatible Function Approximation ICML 2024 On the Hardness of Constrained Cooperative Multi-Agent Reinforcement Learning ICLR 2024 On the Hardness of Online Nonconvex Optimization with Single Oracle Feedback ICLR 2024 Decentralized Robust V-learning for Solving Markov Games with Model Uncertainty JMLR 2023 Generalized-Smooth Nonconvex Optimization is As Efficient As Smooth Nonconvex Optimization ICML 2023 Online Nonconvex Optimization with Limited Instantaneous Oracle Feedback COLT 2023 Data sampling affects the complexity of online SGD over dependent data UAI 2022 Finding Correlated Equilibrium of Constrained Markov Game: A Primal-Dual Approach NeurIPS 2022 Sample Efficient Stochastic Policy Extragradient Algorithm for Zero-Sum Markov Game ICLR 2022 Sample and Communication-Efficient Decentralized Actor-Critic Algorithms with Finite-Time Analysis ICML 2022 Greedy-GQ with Variance Reduction: Finite-time Analysis and Improved Complexity ICLR 2021 Non-Asymptotic Analysis for Two Time-scale TDC with General Smooth Function Approximation NeurIPS 2021 Proximal Gradient Descent-Ascent: Variable Convergence under KŁ Geometry ICLR 2021 A Statistical Mechanics Framework for Task-Agnostic Sample Design in Machine Learning NeurIPS 2020 History-Gradient Aided Batch Size Adaptation for Variance Reduced Algorithms ICML 2020 Proximal Gradient Algorithm with Momentum and Flexible Parameter Restart for Nonconvex Optimization IJCAI 2020 Reanalysis of Variance Reduced Temporal Difference Learning ICLR 2020 Understanding the Impact of Model Incoherence on Convergence of Incremental SGD with Random Reshuffle ICML 2020 Variance-Reduced Off-Policy TDC Learning: Non-Asymptotic Convergence Analysis NeurIPS 2020 A unified variance-reduced accelerated gradient method for convex optimization NeurIPS 2019 Cubic Regularization with Momentum for Nonconvex Optimization UAI 2019 Improved Zeroth-Order Variance Reduced Algorithms and Analysis for Nonconvex Optimization ICML 2019 SGD Converges to Global Minimum in Deep Learning via Star-convex Path ICLR 2019 SpiderBoost and Momentum: Faster Variance Reduction Algorithms NeurIPS 2019 Stochastic Variance-Reduced Cubic Regularization for Nonconvex Optimization AISTATS 2019 Toward Understanding the Impact of Staleness in Distributed Machine Learning ICLR 2019 Convergence of Cubic Regularization for Nonconvex Optimization under KL Property NeurIPS 2018 Critical Points of Linear Neural Networks: Analytical Forms and Landscape Properties ICLR 2018 Distributed Proximal Gradient Algorithm for Partially Asynchronous Computer Clusters JMLR 2018 Conditional Accelerated Lazy Stochastic Gradient Descent ICML 2017 Convergence Analysis of Proximal Gradient with Momentum for Nonconvex Optimization ICML 2017 Learning Latent Space Models with Angular Constraints ICML 2017 On Convergence of Model Parallel Proximal Gradient Algorithm for Stale Synchronous Parallel System AISTATS 2016 Analysis of Robust PCA via Local Incoherence NeurIPS 2015