Olshevsky, Alex

12 publications

AISTATS 2025 MDP Geometry, Normalization and Reward Balancing Solvers Arsenii Mustafin, Aleksei Pakharev, Alex Olshevsky, Ioannis Paschalidis

JMLR 2025 Sample Complexity of the Linear Quadratic Regulator: A Reinforcement Learning Lens Amirreza Neshaei Moghaddam, Alex Olshevsky, Bahman Gharesifard

TMLR 2024 Closing the Gap Between SVRG and TD-SVRG with Gradient Splitting Arsenii Mustafin, Alex Olshevsky, Ioannis Paschalidis

NeurIPS 2023 Convergence of Actor-Critic with Multi-Layer Neural Networks Haoxing Tian, Alex Olshevsky, Yannis Paschalidis

ICLR 2023 On the Performance of Temporal Difference Learning with Neural Networks Haoxing Tian, Ioannis Paschalidis, Alex Olshevsky

JMLR 2022 Asymptotic Network Independence and Step-Size for a Distributed Subgradient Method Alex Olshevsky

NeurIPS 2021 Communication-Efficient SGD: From Local SGD to One-Shot Averaging Artin Spiridonoff, Alex Olshevsky, Yannis Paschalidis

ICML 2021 Temporal Difference Learning as Gradient Splitting Rui Liu, Alex Olshevsky

NeurIPS 2020 Adversarial Crowdsourcing Through Robust Rank-One Matrix Completion Qianqian Ma, Alex Olshevsky

JMLR 2020 Gradient Descent for Sparse Rank-One Matrix Completion for Crowd-Sourced Aggregation of Sparsely Interacting Workers Yao Ma, Alex Olshevsky, Csaba Szepesvari, Venkatesh Saligrama

ICML 2020 Minimax Rate for Learning from Pairwise Comparisons in the BTL Model Julien Hendrickx, Alex Olshevsky, Venkatesh Saligrama

JMLR 2020 Robust Asynchronous Stochastic Gradient-Push: Asymptotically Optimal and Network-Independent Performance for Strongly Convex Functions Artin Spiridonoff, Alex Olshevsky, Ioannis Ch. Paschalidis