Results

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		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	Wed 9:00	Lower Bounds and Nearly Optimal Algorithms in Distributed Learning with Communication Compression Xinmeng Huang · Yiming Chen · Wotao Yin · Kun Yuan
Poster	Wed 9:00	Early Stage Convergence and Global Convergence of Training Mildly Parameterized Neural Networks Mingze Wang · Chao Ma
Poster	Thu 14:00	Using Partial Monotonicity in Submodular Maximization Loay Mualem · Moran Feldman
Workshop		Connectedness of loss landscapes via the lens of Morse theory Danil Akhtiamov · Matt Thomson