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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
Thu 14:00 On Convergence of FedProx: Local Dissimilarity Invariant Bounds, Non-smoothness and Beyond
Xiaotong Yuan · Ping Li
Poster
Wed 14:00 Decomposable Non-Smooth Convex Optimization with Nearly-Linear Gradient Oracle Complexity
Sally Dong · Haotian Jiang · Yin Tat Lee · Swati Padmanabhan · Guanghao Ye
Poster
Wed 9:00 Global Linear and Local Superlinear Convergence of IRLS for Non-Smooth Robust Regression
Liangzu Peng · Christian K├╝mmerle · Rene Vidal
Poster
Thu 14:00 Near-Optimal Goal-Oriented Reinforcement Learning in Non-Stationary Environments
Liyu Chen · Haipeng Luo
Poster
Optimality and Stability in Non-Convex Smooth Games
Guojun Zhang · Pascal Poupart · Yaoliang Yu
Poster
Wed 9:00 Constrained Langevin Algorithms with L-mixing External Random Variables
Yuping Zheng · Andrew Lamperski
Poster
Wed 14:00 The Mechanism of Prediction Head in Non-contrastive Self-supervised Learning
Zixin Wen · Yuanzhi Li
Workshop
The curse of (non)convexity: The case of an Optimization-Inspired Data Pruning algorithm
Fadhel Ayed · Soufiane Hayou
Poster
Wed 9:00 Efficient Non-Parametric Optimizer Search for Diverse Tasks
Ruochen Wang · Yuanhao Xiong · Minhao Cheng · Cho-Jui Hsieh
Poster
Wed 14:00 Gradient Descent Is Optimal Under Lower Restricted Secant Inequality And Upper Error Bound
Charles Guille-Escuret · Adam Ibrahim · Baptiste Goujaud · Ioannis Mitliagkas
Poster
Tue 9:00 From Gradient Flow on Population Loss to Learning with Stochastic Gradient Descent
Christopher De Sa · Satyen Kale · Jason Lee · Ayush Sekhari · Karthik Sridharan