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» Approximation Methods for Supervised Learning
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CORR
2002
Springer
132views Education» more  CORR 2002»
13 years 9 months ago
Robust Feature Selection by Mutual Information Distributions
Mutual information is widely used in artificial intelligence, in a descriptive way, to measure the stochastic dependence of discrete random variables. In order to address question...
Marco Zaffalon, Marcus Hutter
ML
2008
ACM
162views Machine Learning» more  ML 2008»
13 years 10 months ago
Incorporating prior knowledge in support vector regression
This paper explores the addition of constraints to the linear programming formulation of the support vector regression problem for the incorporation of prior knowledge. Equality an...
Fabien Lauer, Gérard Bloch
NECO
2007
127views more  NECO 2007»
13 years 9 months ago
Visual Recognition and Inference Using Dynamic Overcomplete Sparse Learning
We present a hierarchical architecture and learning algorithm for visual recognition and other visual inference tasks such as imagination, reconstruction of occluded images, and e...
Joseph F. Murray, Kenneth Kreutz-Delgado
ECCV
2002
Springer
14 years 12 months ago
Learning Shape from Defocus
We present a novel method for inferring three-dimensional shape from a collection of defocused images. It is based on the observation that defocused images are the null-space of ce...
Paolo Favaro, Stefano Soatto
ICML
2000
IEEE
14 years 10 months ago
Rates of Convergence for Variable Resolution Schemes in Optimal Control
This paper presents a general method to derive tight rates of convergence for numerical approximations in optimal control when we consider variable resolution grids. We study the ...
Andrew W. Moore, Rémi Munos