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» Robust feature extraction via information theoretic learning
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MLDM
1999
Springer
15 years 3 months ago
Non-hierarchical Clustering with Rival Penalized Competitive Learning for Information Retrieval
In large content-based image database applications, e cient information retrieval depends heavily on good indexing structures of the extracted features. While indexing techniques f...
Irwin King, Tak-Kan Lau
FOCS
1999
IEEE
15 years 4 months ago
An Algorithmic Theory of Learning: Robust Concepts and Random Projection
We study the phenomenon of cognitive learning from an algorithmic standpoint. How does the brain effectively learn concepts from a small number of examples despite the fact that e...
Rosa I. Arriaga, Santosh Vempala
ACE
2003
133views Education» more  ACE 2003»
15 years 1 months ago
The Webworkforce - a learning repository to support educators, trainers and Information Technology courses
This paper provides a first account of1 the Building the Internet Workforce project. A number of further papers are planned. An outline of the project’s progress and outcomes is...
John P. Bell, Don Schauder
ADC
2003
Springer
115views Database» more  ADC 2003»
15 years 3 months ago
Document Classification via Structure Synopses
Information available in the Internet is frequently supplied simply as plain ascii text, structured according to orthographic and semantic conventions. Traditional document classi...
Liping Ma, John Shepherd, Anh Nguyen
BMCBI
2008
106views more  BMCBI 2008»
14 years 11 months ago
A machine vision system for automated non-invasive assessment of cell viability via dark field microscopy, wavelet feature selec
Background: Cell viability is one of the basic properties indicating the physiological state of the cell, thus, it has long been one of the major considerations in biotechnologica...
Ning Wei, Erwin Flaschel, Karl Friehs, Tim W. Natt...