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  • title: History-Gradient Aided Batch Size Adaptation for Variance Reduced Algorithms
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            History-Gradient Aided Batch Size Adaptation for Variance Reduced Algorithms
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            History-Gradient Aided Batch Size Adaptation for Variance Reduced Algorithms

            Jul 12, 2020

            Speakers

            KJ

            Kaiyi Ji

            Speaker · 0 followers

            ZW

            Zhe Wang

            Speaker · 0 followers

            BW

            Bowen Weng

            Speaker · 0 followers

            About

            Variance-reduced algorithms, although achieve great theoretical performance, can run slowly in practice due to the periodic gradient estimation with a large batch of data. Batch-size adaptation thus arises as a promising approach to accelerate such algorithms. However, existing schemes either apply prescribed batch-size adaption rule or exploit the information along optimization path via additional backtracking and condition verification steps. In this paper, we propose a novel scheme, which eli…

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