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» Sampling Methods for Unsupervised Learning
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ICML
2007
IEEE
16 years 3 months ago
A recursive method for discriminative mixture learning
We consider the problem of learning density mixture models for classification. Traditional learning of mixtures for density estimation focuses on models that correctly represent t...
Minyoung Kim, Vladimir Pavlovic
97
Voted
ML
2002
ACM
145views Machine Learning» more  ML 2002»
15 years 2 months ago
Boosting Methods for Regression
In this paper we examine ensemble methods for regression that leverage or "boost" base regressors by iteratively calling them on modified samples. The most successful lev...
Nigel Duffy, David P. Helmbold
BMCBI
2010
143views more  BMCBI 2010»
15 years 2 months ago
Learning gene regulatory networks from only positive and unlabeled data
Background: Recently, supervised learning methods have been exploited to reconstruct gene regulatory networks from gene expression data. The reconstruction of a network is modeled...
Luigi Cerulo, Charles Elkan, Michele Ceccarelli
121
Voted
ECCV
2010
Springer
15 years 6 months ago
Learning a Fine Vocabulary
We present a novel similarity measure for bag-of-words type large scale image retrieval. The similarity function is learned in an unsupervised manner, requires no extra space over ...
PERVASIVE
2011
Springer
14 years 5 months ago
Using Decision-Theoretic Experience Sampling to Build Personalized Mobile Phone Interruption Models
We contribute a method for approximating users’ interruptibility costs to use for experience sampling and validate the method in an application that learns when to automatically ...
Stephanie Rosenthal, Anind K. Dey, Manuela M. Velo...