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ICMLA
2009
15 years 1 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
CVPR
2009
IEEE
16 years 11 months ago
Learning Shape Prior Models for Object Matching
The aim of this work is to learn a shape prior model for an object class and to improve shape matching with the learned shape prior. Given images of example instances, we can le...
Cordelia Schmid, Frédéric Jurie, Tin...
ICML
2003
IEEE
16 years 4 months ago
Learning To Cooperate in a Social Dilemma: A Satisficing Approach to Bargaining
Learning in many multi-agent settings is inherently repeated play. This calls into question the naive application of single play Nash equilibria in multi-agent learning and sugges...
Jeff L. Stimpson, Michael A. Goodrich
IWANN
2007
Springer
15 years 10 months ago
Non-parametric Residual Variance Estimation in Supervised Learning
The residual variance estimation problem is well-known in statistics and machine learning with many applications for example in the field of nonlinear modelling. In this paper, we...
Elia Liitiäinen, Amaury Lendasse, Francesco C...
FSMNLP
2008
Springer
15 years 5 months ago
Learning with Weighted Transducers
Weighted finite-state transducers have been used successfully in a variety of natural language processing applications, including speech recognition, speech synthesis, and machine ...
Corinna Cortes, Mehryar Mohri