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Abstract: We address the question of feature selection in the context of visual recognition. It is shown that, besides efficient from a computational standpoint, the infomax principle is nearly optimal in the minimum Bayes error sense. The concept of marginal diversity is introduced, leading to a generic principle for feature selection (the principle of maximum marginal diversity) of extreme computational simplicity. The relationships between infomax and the maximization of marginal diversity are... (Update)
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BibTeX entry: (Update)
Nuno Vasconcelos. Feature selection by maximum marginal diversity: optimality and implications for visual recognition. In Proceedings IEEE Conference On Computer Vision And Pattern Recognition, volume 1, pages 762--769, June 2003. http://citeseer.ist.psu.edu/vasconcelos03feature.html More
@misc{ vasconcelos03feature,
author = "N. Vasconcelos",
title = "Feature selection by maximum marginal diversity: optimality and implications
for visual recognition",
text = "Nuno Vasconcelos. Feature selection by maximum marginal diversity: optimality
and implications for visual recognition. In Proceedings IEEE Conference
On Computer Vision And Pattern Recognition, volume 1, pages 762--769, June
2003.",
year = "2003",
url = "citeseer.ist.psu.edu/vasconcelos03feature.html" }
Citations (may not include all citations):168 Self-Organization in a Perceptual Network (context) - Linsker - 1988
155 An Information Maximisation Approach to Blind Separation and.. - Bell, Sejnowski - 1995
49 on Pattern Analysis and Machine Intelligence (context) - Jain, Zongker et al. - 1997
43 Statistics of Natural Images and Models - Huang, Mumford - 1999
29 Selecting Input Variables using Mutual Information and Nonpa.. - Bonnlander, Weigand - 1994
25 Mutual Information in Learning Feature Transforms - Torkolla, Campbell - 2000
20 Information-Theoretic Learning - Principe, Xu et al. - 2000
11 A Problem of Dimensionality: a Simple Example (context) - Trunk - 1979
7 Minimum Bayes Error Feature Selection for Continuous Speech .. - Saon, Padmanabhan - 2000
7 Texture Modeling and Synthesis using Joint Statistics of Com.. - Portilla, Simoncelli - 1999
6 Information Transfer Through Classifiers and its Relation to.. (context) - Erdogmus, Principe - 2001
4 Data Visualization and Feature Selection: New Algorithms for.. - Yang, Moody - 2000
2 Maximum Entropy and Maximum Likelihood Criteria for Feature .. (context) - Basu, Micchelli et al. - 2000
2 Feature Selection by Maximum Marginal Diversity: Optimality .. - Vasconcelos - 2002
1 What is the Role of Independence for Visual Regognition (context) - Vasconcelos, Carneiro - 2002
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