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Poster
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Wed 14:00
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Sharp Analysis of Stochastic Optimization under Global Kurdyka-Lojasiewicz Inequality
Ilyas Fatkhullin · Jalal Etesami · Niao He · Negar Kiyavash
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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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Tue 9:00
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SAGDA: Achieving O(ϵ−2) Communication Complexity in Federated Min-Max Learning
Haibo Yang · Zhuqing Liu · Xin Zhang · Jia Liu
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Poster
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Thu 14:00
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Stochastic Halpern Iteration with Variance Reduction for Stochastic Monotone Inclusions
Xufeng Cai · Chaobing Song · Cristóbal Guzmán · Jelena Diakonikolas
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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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Thu 14:00
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Adaptive Stochastic Variance Reduction for Non-convex Finite-Sum Minimization
Ali Kavis · Stratis Skoulakis · Kimon Antonakopoulos · Leello Tadesse Dadi · Volkan Cevher
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Poster
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Thu 14:00
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Variance Reduced ProxSkip: Algorithm, Theory and Application to Federated Learning
Grigory Malinovsky · Kai Yi · Peter Richtarik
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Poster
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Tue 14:00
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Multi-block-Single-probe Variance Reduced Estimator for Coupled Compositional Optimization
Wei Jiang · Gang Li · Yibo Wang · Lijun Zhang · Tianbao Yang
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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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Variance Reduction in Off-Policy Deep Reinforcement Learning using Spectral Normalization
Payal Bawa · Rafael Oliveira · Fabio Ramos
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Workshop
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Reducing Communication in Nonconvex Federated Learning with a Novel Single-Loop Variance Reduction Method
Kazusato Oko · Shunta Akiyama · Tomoya Murata · Taiji Suzuki
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Poster
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Tue 9:00
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Gradient Estimation with Discrete Stein Operators
Jiaxin Shi · Yuhao Zhou · Jessica Hwang · Michalis Titsias · Lester Mackey
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