Web: http://arxiv.org/abs/2006.04429

June 20, 2022, 1:11 a.m. | Jingzhao Zhang, Hongzhou Lin, Subhro Das, Suvrit Sra, Ali Jadbabaie

cs.LG updates on arXiv.org arxiv.org

We study oracle complexity of gradient based methods for stochastic
approximation problems. Though in many settings optimal algorithms and tight
lower bounds are known for such problems, these optimal algorithms do not
achieve the best performance when used in practice. We address this
theory-practice gap by focusing on instance-dependent complexity instead of
worst case complexity. In particular, we first summarize known
instance-dependent complexity results and categorize them into three levels. We
identify the domination relation between different levels and propose …

analysis approximation arxiv complexity math stochastic

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