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» Learning Kernel Expansions for Image Classification
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ICML
2007
IEEE
14 years 8 months ago
Self-taught learning: transfer learning from unlabeled data
We present a new machine learning framework called "self-taught learning" for using unlabeled data in supervised classification tasks. We do not assume that the unlabele...
Rajat Raina, Alexis Battle, Honglak Lee, Benjamin ...
CVIU
2008
188views more  CVIU 2008»
13 years 7 months ago
Learning function-based object classification from 3D imagery
We propose a novel scheme for using supervised learning for function-based classification of objects in 3D images. During the learning process, a generic multi-level hierarchical ...
Michael Pechuk, Octavian Soldea, Ehud Rivlin
ICMLA
2009
13 years 5 months ago
Transformation Learning Via Kernel Alignment
This article proposes an algorithm to automatically learn useful transformations of data to improve accuracy in supervised classification tasks. These transformations take the for...
Andrew Howard, Tony Jebara
ICIP
2007
IEEE
14 years 9 months ago
Color Image Superresolution Based on a Stochastic Combinational Classification-Regression Algorithm
Abstract - The proposed algorithm in this work provides superresolution for color images by using a learning based technique that utilizes both generative and discriminant approach...
Karl S. Ni, Truong Q. Nguyen
ICML
2008
IEEE
14 years 8 months ago
Tailoring density estimation via reproducing kernel moment matching
Moment matching is a popular means of parametric density estimation. We extend this technique to nonparametric estimation of mixture models. Our approach works by embedding distri...
Alex J. Smola, Arthur Gretton, Bernhard Schöl...