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 14:00
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Coordinate Linear Variance Reduction for Generalized Linear Programming
Chaobing Song · Cheuk Yin Lin · Stephen Wright · Jelena Diakonikolas
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Workshop
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DRL-EPANET: Deep reinforcement learning for optimal control at scale in Water Distribution Systems
Anas Belfadil · David Modesto · Jose Martin H.
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Poster
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Wed 14:00
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Wasserstein Logistic Regression with Mixed Features
Aras Selvi · Mohammad Reza Belbasi · Martin Haugh · Wolfram Wiesemann
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Poster
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Escaping Saddle Points with Bias-Variance Reduced Local Perturbed SGD for Communication Efficient Nonconvex Distributed Learning
Tomoya Murata · Taiji Suzuki
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Poster
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Wed 14:00
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Adaptive Distribution Calibration for Few-Shot Learning with Hierarchical Optimal Transport
Dandan Guo · Long Tian · He Zhao · Mingyuan Zhou · Hongyuan Zha
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Poster
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Tue 9:00
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Distributed Optimization for Overparameterized Problems: Achieving Optimal Dimension Independent Communication Complexity
Bingqing Song · Ioannis Tsaknakis · Chung-Yiu Yau · Hoi-To Wai · Mingyi Hong
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Workshop
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Graph-Relational Distributionally Robust Optimization
Fengchun Qiao · Xi Peng
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Poster
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Tue 14:00
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EF-BV: A Unified Theory of Error Feedback and Variance Reduction Mechanisms for Biased and Unbiased Compression in Distributed Optimization
Laurent Condat · Kai Yi · Peter Richtarik
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Poster
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Thu 9:00
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A Communication-Efficient Distributed Gradient Clipping Algorithm for Training Deep Neural Networks
Mingrui Liu · Zhenxun Zhuang · Yunwen Lei · Chunyang Liao
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Poster
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Tue 9:00
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Distributed Methods with Compressed Communication for Solving Variational Inequalities, with Theoretical Guarantees
Aleksandr Beznosikov · Peter Richtarik · Michael Diskin · Max Ryabinin · Alexander Gasnikov
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Poster
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Thu 14:00
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Scalable Distributional Robustness in a Class of Non-Convex Optimization with Guarantees
Avinandan Bose · Arunesh Sinha · Tien Mai
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