14 citations · 23 across the 6 of their papers we have counts for
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cs.LG2022
Aggregation in the Mirror Space (AIMS): Fast, Accurate Distributed Machine Learning in Military Settings
Ryan Yang, Haizhou Du, Andre Wibisono +1
Distributed machine learning (DML) can be an important capability for modern military to take advantage of data and devices distributed at multiple vantage points to adapt and lear…
cs.LG2022★ 1 cited
Achieving Efficient Distributed Machine Learning Using a Novel Non-Linear Class of Aggregation Functions
Haizhou Du, Ryan Yang, Yijian Chen +3
Distributed machine learning (DML) over time-varying networks can be an enabler for emerging decentralized ML applications such as autonomous driving and drone fleeting. However, t…
math.ST2022★ 3 cited
Improved analysis for a proximal algorithm for sampling
Yongxin Chen, Sinho Chewi, Adil Salim +1
We study the proximal sampler of Lee, Shen, and Tian (2021) and obtain new convergence guarantees under weaker assumptions than strong log-concavity: namely, our results hold for (…