2 papers
stat.ML2023
Demystifying Disagreement-on-the-Line in High Dimensions
Donghwan Lee, Behrad Moniri, Xinmeng Huang +2
Evaluating the performance of machine learning models under distribution shift is challenging, especially when we only have unlabeled data from the shifted (target) domain, along w…
cs.LG2022
Optimal Complexity in Non-Convex Decentralized Learning over Time-Varying Networks
Xinmeng Huang, Kun Yuan
Decentralized optimization with time-varying networks is an emerging paradigm in machine learning. It saves remarkable communication overhead in large-scale deep training and is mo…