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ICML
2009
IEEE
14 years 9 months ago
Regularization and feature selection in least-squares temporal difference learning
We consider the task of reinforcement learning with linear value function approximation. Temporal difference algorithms, and in particular the Least-Squares Temporal Difference (L...
J. Zico Kolter, Andrew Y. Ng
GECCO
2008
Springer
158views Optimization» more  GECCO 2008»
13 years 9 months ago
Objective reduction using a feature selection technique
This paper introduces two new algorithms to reduce the number of objectives in a multiobjective problem by identifying the most conflicting objectives. The proposed algorithms ar...
Antonio López Jaimes, Carlos A. Coello Coel...
3DPVT
2006
IEEE
187views Visualization» more  3DPVT 2006»
14 years 15 days ago
Linking Feature Lines on 3D Triangle Meshes with Artificial Potential Fields
We propose artificial potential fields as a support theory for a feature linking algorithm. This algorithm operates on 3D triangle meshes derived from multiple range scans of an o...
David L. Page, Andreas Koschan, Mongi A. Abidi
CVPR
2003
IEEE
14 years 10 months ago
Extracting Dense Features for Visual Correspondence with Graph Cuts
We present a method for extracting dense features from stereo and motion sequences. Our dense feature is defined symmetrically with respect to both images, and it is extracted dur...
Olga Veksler
ICCCN
2007
IEEE
13 years 9 months ago
Online Selection of Tracking Features using AdaBoost
In this paper, a novel feature selection algorithm for object tracking is proposed. This algorithm performs more robust than the previous works by taking the correlation between f...
Ying-Jia Yeh, Chiou-Ting Hsu