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Workshop
Private Stochastic Optimization With Large Worst-Case Lipschitz Parameter: Optimal Rates for (Non-Smooth) Convex Losses & Extension to Non-Convex Losses
Andrew Lowy · Meisam Razaviyayn
Poster
Wed 14:00 The Mechanism of Prediction Head in Non-contrastive Self-supervised Learning
Zixin Wen · Yuanzhi Li
Poster
Wed 9:00 Constrained Langevin Algorithms with L-mixing External Random Variables
Yuping Zheng · Andrew Lamperski
Poster
Thu 14:00 On Convergence of FedProx: Local Dissimilarity Invariant Bounds, Non-smoothness and Beyond
Xiaotong Yuan · Ping Li
Poster
Thu 9:00 Better SGD using Second-order Momentum
Hoang Tran · Ashok Cutkosky
Poster
Wed 9:00 Asynchronous SGD Beats Minibatch SGD Under Arbitrary Delays
Konstantin Mishchenko · Francis Bach · Mathieu Even · Blake Woodworth
Poster
Thu 14:00 Adaptive Stochastic Variance Reduction for Non-convex Finite-Sum Minimization
Ali Kavis · Stratis Skoulakis · Kimon Antonakopoulos · Leello Tadesse Dadi · Volkan Cevher
Poster
Optimality and Stability in Non-Convex Smooth Games
Guojun Zhang · Pascal Poupart · Yaoliang Yu
Workshop
Optimal Complexity in Non-Convex Decentralized Learning over Time-Varying Networks
Xinmeng Huang · Kun Yuan
Poster
Thu 14:00 Distributed Distributionally Robust Optimization with Non-Convex Objectives
Yang Jiao · Kai Yang · Dongjin Song
Poster
Tue 14:00 Multi-block-Single-probe Variance Reduced Estimator for Coupled Compositional Optimization
Wei Jiang · Gang Li · Yibo Wang · Lijun Zhang · Tianbao Yang
Poster
Wed 9:00 Lower Bounds and Nearly Optimal Algorithms in Distributed Learning with Communication Compression
Xinmeng Huang · Yiming Chen · Wotao Yin · Kun Yuan