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ALGORITHMICA
2006
74views more  ALGORITHMICA 2006»
15 years 7 months ago
Parallelizing Feature Selection
Classification is a key problem in machine learning/data mining. Algorithms for classification have the ability to predict the class of a new instance after having been trained on...
Jerffeson Teixeira de Souza, Stan Matwin, Nathalie...
TKDE
2008
111views more  TKDE 2008»
15 years 6 months ago
Text Clustering with Feature Selection by Using Statistical Data
Abstract-- Feature selection is an important method for improving the efficiency and accuracy of text categorization algorithms by removing redundant and irrelevant terms from the ...
Yanjun Li, Congnan Luo, Soon M. Chung
MVA
2007
309views Computer Vision» more  MVA 2007»
15 years 6 months ago
Robust Facial Feature Extraction Using Embedded Hidden Markov Model for Face Recognition under Large Pose Variation
We propose an algorithm for extracting facial features robustly from images for face recognition under large pose variation. Rectangular facial features are retrieved via the by-p...
Ping-Han Lee, Yun-Wen Wang, Jison Hsu, Ming-Hsuan ...
BMVC
2010
15 years 4 months ago
Discriminative Topics Modelling for Action Feature Selection and Recognition
This paper presents a framework for recognising realistic human actions captured from unconstrained environments. The novelties of this work lie in three aspects. First, we propos...
Matteo Bregonzio, Jian Li, Shaogang Gong, Tao Xian...
ISDA
2010
IEEE
15 years 4 months ago
Feature selection is the ReliefF for multiple instance learning
Dimensionality reduction and feature selection in particular are known to be of a great help for making supervised learning more effective and efficient. Many different feature sel...
Amelia Zafra, Mykola Pechenizkiy, Sebastián...