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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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Theoretically Better and Numerically Faster Distributed Optimization with Smoothness-Aware Quantization Techniques
Bokun Wang · Mher Safaryan · Peter Richtarik
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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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Workshop
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Smoothed-SGDmax: A Stability-Inspired Algorithm to Improve Adversarial Generalization
Jiancong Xiao · Jiawei Zhang · Zhiquan Luo · Asuman Ozdaglar
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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 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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Tue 14:00
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Differentially Private Online-to-batch for Smooth Losses
Qinzi Zhang · Hoang Tran · Ashok Cutkosky
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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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Tue 9:00
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Accelerated Primal-Dual Gradient Method for Smooth and Convex-Concave Saddle-Point Problems with Bilinear Coupling
Dmitry Kovalev · Alexander Gasnikov · Peter Richtarik
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Poster
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Thu 9:00
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Revisiting Optimal Convergence Rate for Smooth and Non-convex Stochastic Decentralized Optimization
Kun Yuan · Xinmeng Huang · Yiming Chen · Xiaohan Zhang · Yingya Zhang · Pan Pan
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Poster
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Thu 9:00
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Not too little, not too much: a theoretical analysis of graph (over)smoothing
Nicolas Keriven
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Poster
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Tue 9:00
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Randomized Message-Interception Smoothing: Gray-box Certificates for Graph Neural Networks
Yan Scholten · Jan Schuchardt · Simon Geisler · Aleksandar Bojchevski · Stephan Günnemann
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