Results

Poster	Tue 9:00	Distributed Methods with Compressed Communication for Solving Variational Inequalities, with Theoretical Guarantees Aleksandr Beznosikov · Peter Richtarik · Michael Diskin · Max Ryabinin · Alexander Gasnikov
Poster	Tue 14:00	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
Poster	Thu 14:00	Variance Reduced ProxSkip: Algorithm, Theory and Application to Federated Learning Grigory Malinovsky · Kai Yi · Peter Richtarik
Poster	Tue 9:00	Fine-tuning Language Models over Slow Networks using Activation Quantization with Guarantees Jue WANG · Binhang Yuan · Luka Rimanic · Yongjun He · Tri Dao · Beidi Chen · Christopher Ré · Ce Zhang
Workshop		Distributed Newton-Type Methods with Communication Compression and Bernoulli Aggregation Rustem Islamov · Xun Qian · Slavomír Hanzely · Mher Safaryan · Peter Richtarik
Workshop		Stochastic Gradient Methods with Compressed Communication for Decentralized Saddle Point Problems Chhavi Sharma · Vishnu Narayanan · Balamurugan Palaniappan
Poster	Tue 14:00	BEER: Fast $O(1/T)$ Rate for Decentralized Nonconvex Optimization with Communication Compression Haoyu Zhao · Boyue Li · Zhize Li · Peter Richtarik · Yuejie Chi
Poster		Distributed Online Convex Optimization with Compressed Communication Zhipeng Tu · Xi Wang · Yiguang Hong · Lei Wang · Deming Yuan · Guodong Shi
Poster	Tue 9:00	SoteriaFL: A Unified Framework for Private Federated Learning with Communication Compression Zhize Li · Haoyu Zhao · Boyue Li · Yuejie Chi
Poster	Wed 9:00	Lower Bounds and Nearly Optimal Algorithms in Distributed Learning with Communication Compression Xinmeng Huang · Yiming Chen · Wotao Yin · Kun Yuan