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cs.LG2025
Strategies for Improving Communication Efficiency in Distributed and Federated Learning: Compression, Local Training, and Personalization
Kai Yi
Distributed and federated learning are essential paradigms for training models across decentralized data sources while preserving privacy, yet communication overhead remains a majo…
cs.LG2025
Symmetric Pruning of Large Language Models
Kai Yi, Peter Richtárik
Popular post-training pruning methods such as Wanda and RIA are known for their simple, yet effective, designs that have shown exceptional empirical performance. Wanda optimizes pe…