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» Minimax Probability Machine
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ECML
2003
Springer
14 years 3 months ago
Optimizing Local Probability Models for Statistical Parsing
Abstract. This paper studies the properties and performance of models for estimating local probability distributions which are used as components of larger probabilistic systems â€...
Kristina Toutanova, Mark Mitchell, Christopher D. ...
ICML
2006
IEEE
14 years 11 months ago
Nightmare at test time: robust learning by feature deletion
When constructing a classifier from labeled data, it is important not to assign too much weight to any single input feature, in order to increase the robustness of the classifier....
Amir Globerson, Sam T. Roweis
ICML
2005
IEEE
14 years 11 months ago
Learning to compete, compromise, and cooperate in repeated general-sum games
Learning algorithms often obtain relatively low average payoffs in repeated general-sum games between other learning agents due to a focus on myopic best-response and one-shot Nas...
Jacob W. Crandall, Michael A. Goodrich
COLT
2008
Springer
14 years 6 days ago
On the Equivalence of Weak Learnability and Linear Separability: New Relaxations and Efficient Boosting Algorithms
Boosting algorithms build highly accurate prediction mechanisms from a collection of lowaccuracy predictors. To do so, they employ the notion of weak-learnability. The starting po...
Shai Shalev-Shwartz, Yoram Singer
COLT
2010
Springer
13 years 8 months ago
Convex Games in Banach Spaces
We study the regret of an online learner playing a multi-round game in a Banach space B against an adversary that plays a convex function at each round. We characterize the minima...
Karthik Sridharan, Ambuj Tewari