no code implementations • NeurIPS 2021 • Xinmeng Huang, Kun Yuan, Xianghui Mao, Wotao Yin
In this paper, we will improve the convergence analysis and rates of variance reduction under without-replacement sampling orders for composite finite-sum minimization. Our results are in two-folds.
no code implementations • 25 Apr 2021 • Xinmeng Huang, Kun Yuan, Xianghui Mao, Wotao Yin
In the highly data-heterogeneous scenario, Prox-DFinito with optimal cyclic sampling can attain a sample-size-independent convergence rate, which, to our knowledge, is the first result that can match with uniform-iid-sampling with variance reduction.
