What is it about?
This paper proposes a randomized subgradient method to solve convex optimization problems providing convergence results.
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Why is it important?
The paper introduces randomness to a subgradient method to solve convex optimization problems.
Perspectives
This paper follows the idea of the paper entitled "Approximating subdifferentials by random sampling of gradients" by J. V. Burke, A. S. Lewis, and M. L. Overton, published in Mathematics of Operations Research in 2002.
Dr Chee Khian Sim
University of Portsmouth
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This page is a summary of: A Subgradient Method Based on Gradient Sampling for Solving Convex Optimization Problems, Numerical Functional Analysis and Optimization, September 2015, Taylor & Francis,
DOI: 10.1080/01630563.2015.1086788.
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