Accelerating SGD using flexible variance reduction on large-scale datasets

Author:

Tang Mingxing,Qiao Linbo,Huang ZhenORCID,Liu Xinwang,Peng Yuxing,Liu Xueliang

Publisher

Springer Science and Business Media LLC

Subject

Artificial Intelligence,Software

Reference40 articles.

1. Roux NL, Schmidt M, Bach FR (2012) A stochastic gradient method with an exponential convergence rate for finite training sets. Adv Neural Inf Process Syst 2012:2663–2671

2. Reddi SJ, Hefny A, Sra S, Poczos B, Smola AJ (2015) On variance reduction in stochastic gradient descent and its asynchronous variants. Adv Neural Inf Process Syst 2015:2647–2655

3. Schmidt M, Le Roux N, Bach F (2017) Minimizing finite sums with the stochastic average gradient. Math Program 162(1–2):83–112

4. Defazio A, Bach F, Lacoste-Julien S (2014) SAGA: a fast incremental gradient method with support for non-strongly convex composite objectives. Adv Neural Inf Process Syst 2014:1646–1654

5. De S, Goldstein T (2016) Efficient distributed SGD with variance reduction. In: 2016 IEEE 16th international conference on data mining (ICDM), 2016. pp 111–120

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