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CVPR
2004
IEEE
14 years 10 months ago
Learning Classifiers from Imbalanced Data Based on Biased Minimax Probability Machine
We consider the problem of the binary classification on imbalanced data, in which nearly all the instances are labelled as one class, while far fewer instances are labelled as the...
Kaizhu Huang, Haiqin Yang, Irwin King, Michael R. ...
BMCBI
2004
140views more  BMCBI 2004»
13 years 8 months ago
What can we learn from noncoding regions of similarity between genomes?
Background: In addition to known protein-coding genes, large amounts of apparently non-coding sequence are conserved between the human and mouse genomes. It seems reasonable to as...
Thomas A. Down, Tim J. P. Hubbard
AI
2000
Springer
13 years 8 months ago
Learning to construct knowledge bases from the World Wide Web
The World Wide Web is a vast source of information accessible to computers, but understandable only to humans. The goal of the research described here is to automatically create a...
Mark Craven, Dan DiPasquo, Dayne Freitag, Andrew M...
KDD
1997
ACM
169views Data Mining» more  KDD 1997»
14 years 29 days ago
Learning to Extract Text-Based Information from the World Wide Web
Thereis a wealthof informationto be minedfromnarrative text on the WorldWideWeb.Unfortunately, standard natural language processing (NLP)extraction techniques expect full, grammat...
Stephen Soderland
ICPR
2002
IEEE
14 years 10 months ago
Bayesian Pot-Assembly from Fragments as Problems in Perceptual-Grouping and Geometric-Learning
A heretofore unsolved problem of great archaeological importance is the automatic assembly of pots made on a wheel from the hundreds (or thousands) of sherds found at an excavatio...
David B. Cooper, Andrew R. Willis, Stuart Andrews,...