Thursday, Oct 4, 2:15pm, WWH-1314

  SPEAKER:
  Yishay Mansour, Google amd Tel Aviv University

  TITLE:
  Regret Minimization: Algorithms and Applications

  ABSTRACT: 
  Consider an agent that has to select between multiple actions, where
  at each time step the agent selects a distribution over actions, and
  the adversary selects a vector of payoff for the actions.  (The
  adversary observes the agents distribution before selecting its
  action.)  The external regret is define as the difference between
  the payoff of the best action and the agents payoff. A basic result
  in regret minimization is that the agent can achieve a performance
  which is near the best single action, namely, the average regret
  vanishes.

  In this talk we will derive regret minimization algorithms, from
  basic principles.  In addition we will consider the more involved
  notion of internal regret, and relate it to game theoretic notations
  (such as avoiding dominated actions and converging to a correlated
  equilibria).

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