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ENTITY Adversarial Bandit Optimization with Globally Bounded Perturbations to Convex Losses

Adversarial Bandit Optimization with Globally Bounded Perturbations to Convex Losses

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  1. RESEARCH · CL_93826 ·

    New research explores adversarial bandit optimization with bounded perturbations and distributed agents

    Two new research papers explore adversarial bandit optimization, a machine learning technique where losses can be non-convex and non-smooth. The first paper introduces a framework for globally budgeted perturbations to …