Controlling stochastic gradient descent using stochastic approximation for robust distributed optimization

Author:

Jain Adit,Krishnamurthy Vikram1

Affiliation:

1. Cornell University, Ithaca, NY, United States

Publisher

American Institute of Mathematical Sciences (AIMS)

Reference26 articles.

1.

Constrained Markov Decision Processes | Eitan Altman | Taylor & Francis, URL https://www.taylorfrancis.com/books/mono/10.1201/9781315140223/constrained-markov-decision-processes-eitan-altman.

2.

A. Ajalloeian and S. U. Stich, On the convergence of SGD with biased gradients, 2021, http://arXiv.org/abs/2008.00051.

3.

E. Altman, B. Gaujal and A. Hordijk, Discrete-Event Control of Stochastic Networks: Multimodularityand Regularity, Springer, 2003.

4.

P. Bachman, A. Sordoni and A. Trischler, Learning algorithms for active learning, in Proceedings of the 34th International Conference on Machine Learning, PMLR, 2017,301-310, https://proceedings.mlr.press/v70/bachman17a.html, ISSN: 2640-3498.

5. Optimal policies for controlled Markov chains with a constraint

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