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Machine Learning, Volume 67, 2007

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Volume 67, Numbers 1-2, May 2007

Special Issue on Learning & Computational Game Theory

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Amy Greenwald, Michael L. Littman:
Introduction to the special issue on learning and computational game theory. 3-6
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Elchanan Mossel, Sébastien Roch:
Slow emergence of cooperation for win-stay lose-shift on trees. 7-22
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Vincent Conitzer, Tuomas Sandholm:
AWESOME: A general multiagent learning algorithm that converges in self-play and learns a best response against stationary opponents. 23-43
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Rob Powers, Yoav Shoham, Thuc Vu:
A general criterion and an algorithmic framework for learning in multi-agent systems. 45-76
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Shie Mannor, Jeff S. Shamma, Gürdal Arslan:
Online calibrated forecasts: Memory efficiency versus universality for learning in games. 77-115
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Albert Xin Jiang, Kevin Leyton-Brown:
Bidding agents for online auctions with hidden bids. 117-143
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Yevgeniy Vorobeychik, Michael P. Wellman, Satinder Singh:
Learning payoff functions in infinite games. 145-168

Volume 67, Number 3, June 2007

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Jussi Klemelä:
Density estimation with stagewise optimization of the empirical risk. 169-195
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Don R. Hush, Clint Scovel, Ingo Steinwart:
Stability of Unstable Learning Algorithms. 197-206
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Rong Jin, Jian Zhang:
Multi-Class Learning by Smoothed Boosting. 207-227

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