Entropic risk-averse generalized momentum methods

Optimization Methods and Software, 40(6), pp. 1535–1583, 2025.

Publisher (DOI)Code

Builds a unified convergence and risk analysis for the generalized momentum family (covering gradient descent, heavy ball, and Nesterov acceleration) under stochastic gradient errors, bounding the entropic risk and entropic value-at-risk of suboptimality. The bounds support risk-averse parameter selection (RA-GMM): choosing step and momentum on the rate–risk Pareto frontier rather than for expected performance alone.

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