68 citations · 143 across the 8 of their papers we have counts for
8 papers
Convergence and Privacy of Decentralized Nonconvex Optimization with Gradient Clipping and Communication Compression
Boyue Li, Yuejie Chi
Achieving communication efficiency in decentralized machine learning has been attracting significant attention, with communication compression recognized as an effective technique…
SoteriaFL: A Unified Framework for Private Federated Learning with Communication Compression
Zhize Li, Haoyu Zhao, Boyue Li +1
To enable large-scale machine learning in bandwidth-hungry environments such as wireless networks, significant progress has been made recently in designing communication-efficient…
BEER: Fast Rate for Decentralized Nonconvex Optimization with Communication Compression
Haoyu Zhao, Boyue Li, Zhize Li +2
Communication efficiency has been widely recognized as the bottleneck for large-scale decentralized machine learning applications in multi-agent or federated environments. To tackl…
Factored couplings in multi-marginal optimal transport via difference of convex programming
Quang Huy Tran, Hicham Janati, Ievgen Redko +2
Optimal transport (OT) theory underlies many emerging machine learning (ML) methods nowadays solving a wide range of tasks such as generative modeling, transfer learning and inform…
A Large Collection of Real-world Pediatric Sleep Studies
Harlin Lee, Boyue Li, Shelly DeForte +4
Despite being crucial to health and quality of life, sleep -- especially pediatric sleep -- is not yet well understood. This is exacerbated by lack of access to sufficient pediatri…
Communication-Efficient Distributed Optimization in Networks with Gradient Tracking and Variance Reduction
Boyue Li, Shicong Cen, Yuxin Chen +1
There is growing interest in large-scale machine learning and optimization over decentralized networks, e.g. in the context of multi-agent learning and federated learning. Due to t…