We develop recursive, data-driven, stochastic subgradient methods for optimizing a new, versatile, and application-driven class of convex risk measures, termed here as mean-semideviations, strictly generalizing the well-known and popular mean-upper-semideviation. We introduce the MESSAGEp algorithm, which is an efficie…
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New algorithm tackles risk-aware learning problems efficiently.
problem Risk-aware learning with mean-semideviation objective.
method Zeroth-order compositional stochastic optimization algorithm.
result Algorithm converges to optimal solutions with explicit rates.