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» A supervised learning approach for imbalanced data sets
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ICPR
2002
IEEE
16 years 5 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,...
JMLR
2011
192views more  JMLR 2011»
14 years 11 months ago
Minimum Description Length Penalization for Group and Multi-Task Sparse Learning
We propose a framework MIC (Multiple Inclusion Criterion) for learning sparse models based on the information theoretic Minimum Description Length (MDL) principle. MIC provides an...
Paramveer S. Dhillon, Dean P. Foster, Lyle H. Unga...
ICASSP
2011
IEEE
14 years 8 months ago
Online Kernel SVM for real-time fMRI brain state prediction
The Support Vector Machine (SVM) methodology is an effective, supervised, machine learning method that gives stateof-the-art performance for brain state classification from funct...
Yongxin Taylor Xi, Hao Xu, Ray Lee, Peter J. Ramad...
RECOMB
2008
Springer
16 years 5 months ago
Bootstrapping the Interactome: Unsupervised Identification of Protein Complexes in Yeast
Protein interactions and complexes are major components of biological systems. Recent genome-wide applications of tandem affinity purification (TAP) in yeast have increased signifi...
Caroline C. Friedel, Jan Krumsiek, Ralf Zimmer
ICASSP
2010
IEEE
15 years 4 months ago
Discriminative training methods for language models using conditional entropy criteria
This paper addresses the problem of discriminative training of language models that does not require any transcribed acoustic data. We propose to minimize the conditional entropy ...
Jui-Ting Huang, Xiao Li, Alex Acero