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PR
2006
83views more  PR 2006»
13 years 7 months ago
Optimal convex error estimators for classification
A cross-validation error estimator is obtained by repeatedly leaving out some data points, deriving classifiers on the remaining points, computing errors for these classifiers on ...
Chao Sima, Edward R. Dougherty
ICML
2008
IEEE
14 years 8 months ago
No-regret learning in convex games
Quite a bit is known about minimizing different kinds of regret in experts problems, and how these regret types relate to types of equilibria in the multiagent setting of repeated...
Geoffrey J. Gordon, Amy R. Greenwald, Casey Marks
CVPR
2009
IEEE
15 years 2 months ago
Convexity and Bayesian Constrained Local Models
The accurate localization of facial features plays a fundamental role in any face recognition pipeline. Constrained local models (CLM) provide an effective approach to localizati...
Ulrich Paquet (Imense Ltd)
MOR
2006
81views more  MOR 2006»
13 years 7 months ago
Simulated Annealing for Convex Optimization
We apply the method known as simulated annealing to the following problem in convex optimization: minimize a linear function over an arbitrary convex set, where the convex set is ...
Adam Tauman Kalai, Santosh Vempala
ICML
2008
IEEE
14 years 8 months ago
Random classification noise defeats all convex potential boosters
A broad class of boosting algorithms can be interpreted as performing coordinate-wise gradient descent to minimize some potential function of the margins of a data set. This class...
Philip M. Long, Rocco A. Servedio