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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 9:00
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Non-convex online learning via algorithmic equivalence
Udaya Ghai · Zhou Lu · Elad Hazan
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Workshop
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Federated Frank-Wolfe Algorithm
Ali Dadras · Karthik Prakhya · Alp Yurtsever
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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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Momentum Aggregation for Private Non-convex ERM
Hoang Tran · Ashok Cutkosky
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Poster
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Thu 14:00
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A framework for bilevel optimization that enables stochastic and global variance reduction algorithms
Mathieu Dagréou · Pierre Ablin · Samuel Vaiter · Thomas Moreau
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Poster
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Tue 14:00
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Online PAC-Bayes Learning
Maxime Haddouche · Benjamin Guedj
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Poster
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Tue 14:00
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Fast Stochastic Composite Minimization and an Accelerated Frank-Wolfe Algorithm under Parallelization
Benjamin Dubois-Taine · Francis Bach · Quentin Berthet · Adrien Taylor
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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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Thu 9:00
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Zeroth-Order Negative Curvature Finding: Escaping Saddle Points without Gradients
Hualin Zhang · Huan Xiong · Bin Gu
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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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Workshop
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Boosting as Frank-Wolfe
Ryotaro Mitsuboshi · Kohei Hatano · Eiji Takimoto
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