Convex Repeated Games and Fenchel Duality
Shai Shalev-Shwartz and Yoram Singer
In: NIPS 2006, 5-10 Dec 2006, Vancouver, CA.

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Abstract

We describe and analyze an algorithmic framework for playing convex repeated games. In each trial of the repeated game, the first player predicts a vector and then the second player responds with a loss function for the vector. We describe a generalization of Fenchel duality, which is used to derive an algorithmic framework for the first player and analyze the player's regret. We then use our algorithmic framework and its corresponding regret analysis for analyzing online learning and boosting algorithms.

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• Convex Repeated Games and Fenchel Duality (deposited 22 November 2006) [Currently Displayed]
  • Convex Repeated Games and Fenchel Duality (deposited 12 September 2007)

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