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ECCV
2008
Springer
14 years 9 months ago
Efficiently Learning Random Fields for Stereo Vision with Sparse Message Passing
As richer models for stereo vision are constructed, there is a growing interest in learning model parameters. To estimate parameters in Markov Random Field (MRF) based stereo formu...
Jerod J. Weinman, Lam Tran, Christopher J. Pal
IJCAI
2003
13 years 9 months ago
Approximate Policy Iteration using Large-Margin Classifiers
We present an approximate policy iteration algorithm that uses rollouts to estimate the value of each action under a given policy in a subset of states and a classifier to general...
Michail G. Lagoudakis, Ronald Parr
ICML
2006
IEEE
14 years 8 months ago
Iterative RELIEF for feature weighting
RELIEF is considered one of the most successful algorithms for assessing the quality of features. In this paper, we propose a set of new feature weighting algorithms that perform s...
Yijun Sun, Jian Li
AI
2009
Springer
14 years 2 months ago
An Iterative Hybrid Filter-Wrapper Approach to Feature Selection for Document Clustering
The manipulation of large-scale document data sets often involves the processing of a wealth of features that correspond with the available terms in the document space. The employm...
Mohammad-Amin Jashki, Majid Makki, Ebrahim Bagheri...
SARA
2005
Springer
14 years 1 months ago
Feature-Discovering Approximate Value Iteration Methods
Sets of features in Markov decision processes can play a critical role ximately representing value and in abstracting the state space. Selection of features is crucial to the succe...
Jia-Hong Wu, Robert Givan