🏢 Bocconi University

This paper introduces a novel framework for learning-augmented algorithms that improves performance by integrating the learning process into the algorithm itself, rather than treating the predictor as…

This paper presents a novel, UCB-like algorithm for bandits with stochastic and adversarial constraints, achieving optimal performance without the stringent assumptions of prior primal-dual methods.