178 citations · 987 across the 31 of their papers we have counts for
Showing 2018Show all
3 papers · 1 filter
cs.DC2018★ 20 cited
Distributed Learning over Unreliable Networks
Chen Yu, Hanlin Tang, Cedric Renggli +5
Most of today's distributed machine learning systems assume {\em reliable networks}: whenever two machines exchange information (e.g., gradients or models), the network should guar…
cs.DC2018★ 175 cited
D: Decentralized Training over Decentralized Data
Hanlin Tang, Xiangru Lian, Ming Yan +2
While training a machine learning model using multiple workers, each of which collects data from their own data sources, it would be most useful when the data collected from differ…
cs.LG2018★ 178 cited
Communication Compression for Decentralized Training
Hanlin Tang, Shaoduo Gan, Ce Zhang +2
Optimizing distributed learning systems is an art of balancing between computation and communication. There have been two lines of research that try to deal with slower networks: {…