Given any algorithm for convex optimization that uses exact first-order information (i.e., function values and subgradients), we show how to use such an algorithm to solve the problem with access to ...
Abstract: We consider structured online convex optimization (OCO) with bandit feedback, where either the loss function is smooth or the constraint set is strongly convex. Projection-free methods are ...
Convex optimisation constitutes a fundamental area in applied mathematics where the objective is to identify the minimum of a convex function subject to a set of convex constraints. This framework ...
Convex geometry and combinatorial optimisation form a vibrant nexus of research that bridges theoretical mathematics with practical algorithm design. The study of convex sets and their structural ...
https://doi.org/10.4169/amer.math.monthly.118.07.636 • https://www.jstor.org/stable/10.4169/amer.math.monthly.118.07.636 Copy URL Abstract This note provides an ...
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