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Workshop
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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
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Poster
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Thu 14:00
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On Convergence of FedProx: Local Dissimilarity Invariant Bounds, Non-smoothness and Beyond
Xiaotong Yuan · Ping Li
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Poster
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Wed 14:00
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Decomposable Non-Smooth Convex Optimization with Nearly-Linear Gradient Oracle Complexity
Sally Dong · Haotian Jiang · Yin Tat Lee · Swati Padmanabhan · Guanghao Ye
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Poster
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Wed 9:00
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Global Linear and Local Superlinear Convergence of IRLS for Non-Smooth Robust Regression
Liangzu Peng · Christian Kümmerle · Rene Vidal
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Poster
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Optimality and Stability in Non-Convex Smooth Games
Guojun Zhang · Pascal Poupart · Yaoliang Yu
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Poster
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Wed 14:00
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The Mechanism of Prediction Head in Non-contrastive Self-supervised Learning
Zixin Wen · Yuanzhi Li
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Poster
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Wed 9:00
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Constrained Langevin Algorithms with L-mixing External Random Variables
Yuping Zheng · Andrew Lamperski
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Poster
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Thu 9:00
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Better SGD using Second-order Momentum
Hoang Tran · Ashok Cutkosky
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Workshop
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Optimal Complexity in Non-Convex Decentralized Learning over Time-Varying Networks
Xinmeng Huang · Kun Yuan
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Poster
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Thu 14:00
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Distributed Distributionally Robust Optimization with Non-Convex Objectives
Yang Jiao · Kai Yang · Dongjin Song
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Poster
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Wed 9:00
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Lower Bounds and Nearly Optimal Algorithms in Distributed Learning with Communication Compression
Xinmeng Huang · Yiming Chen · Wotao Yin · Kun Yuan
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Poster
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Wed 9:00
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Early Stage Convergence and Global Convergence of Training Mildly Parameterized Neural Networks
Mingze Wang · Chao Ma
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