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» Robust Feature Selection Algorithms
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BMCBI
2007
123views more  BMCBI 2007»
13 years 9 months ago
Robust clustering in high dimensional data using statistical depths
Background: Mean-based clustering algorithms such as bisecting k-means generally lack robustness. Although componentwise median is a more robust alternative, it can be a poor cent...
Yuanyuan Ding, Xin Dang, Hanxiang Peng, Dawn Wilki...
CVPR
2007
IEEE
14 years 11 months ago
Eigenboosting: Combining Discriminative and Generative Information
A major shortcoming of discriminative recognition and detection methods is their noise sensitivity, both during training and recognition. This may lead to very sensitive and britt...
Helmut Grabner, Peter M. Roth, Horst Bischof
WEBI
2005
Springer
14 years 3 months ago
A Semi-Supervised Document Clustering Algorithm Based on EM
Document clustering is a very hard task in Automatic Text Processing since it requires to extract regular patterns from a document collection without a priori knowledge on the cat...
Leonardo Rigutini, Marco Maggini
ISI
2007
Springer
14 years 3 months ago
FACT: Fast Algorithm for Categorizing Text
— With the ever-increasing number of digital documents, the ability to automatically classifying those documents both quickly and accurately is becoming more critical and difficu...
Saket S. R. Mengle, Nazli Goharian, Alana Platt
ITS
2010
Springer
157views Multimedia» more  ITS 2010»
14 years 2 months ago
A Computational Model of Accelerated Future Learning through Feature Recognition
Accelerated future learning, in which learning proceeds more effectively and more rapidly because of prior learning, is considered to be one of the most interesting measures of ro...
Nan Li, William W. Cohen, Kenneth R. Koedinger