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ICML
2003
IEEE
14 years 10 months ago
Planning in the Presence of Cost Functions Controlled by an Adversary
We investigate methods for planning in a Markov Decision Process where the cost function is chosen by an adversary after we fix our policy. As a running example, we consider a rob...
H. Brendan McMahan, Geoffrey J. Gordon, Avrim Blum
CVPR
2006
IEEE
14 years 3 months ago
Estimating Intrinsic Component Images using Non-Linear Regression
Images can be represented as the composition of multiple intrinsic component images, such as shading, albedo, and noise images. In this paper, we present a method for estimating i...
Marshall F. Tappen, Edward H. Adelson, William T. ...
JMLR
2008
133views more  JMLR 2008»
13 years 9 months ago
Algorithms for Sparse Linear Classifiers in the Massive Data Setting
Classifiers favoring sparse solutions, such as support vector machines, relevance vector machines, LASSO-regression based classifiers, etc., provide competitive methods for classi...
Suhrid Balakrishnan, David Madigan
SIAMJO
2008
104views more  SIAMJO 2008»
13 years 9 months ago
A Minimax Theorem with Applications to Machine Learning, Signal Processing, and Finance
This paper concerns a fractional function of the form xT a/ xT Bx, where B is positive definite. We consider the game of choosing x from a convex set, to maximize the function, an...
Seung-Jean Kim, Stephen P. Boyd
MCS
2005
Springer
14 years 3 months ago
A Probability Model for Combining Ranks
Mixed Group Ranks is a parametric method for combining rank based classiers that is eective for many-class problems. Its parametric structure combines qualities of voting methods...
Ofer Melnik, Yehuda Vardi, Cun-Hui Zhang