bandits

Optimism in the Face of Ambiguity Principle for Multi-Armed Bandits

  • Mengmeng Li
  • Daniel Kuhn
  • Bahar TaČ™kesen
    • Categories Convex Optimization, Data Science Algorithms, Data Science Applications Tags , ,

    \(\) Follow-The-Regularized-Leader (FTRL) algorithms often enjoy optimal regret for adversarial as well as stochastic bandit problems and allow for a streamlined analysis. However, FTRL algorithms require the solution of an optimization problem in every iteration and are thus computationally challenging. In contrast, Follow-The-Perturbed-Leader (FTPL) algorithms achieve computational efficiency by perturbing the estimates of the rewards … Read more