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» A Framework for Multiple-Instance Learning
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ICML
2006
IEEE
16 years 7 months ago
Iterative RELIEF for feature weighting
RELIEF is considered one of the most successful algorithms for assessing the quality of features. In this paper, we propose a set of new feature weighting algorithms that perform s...
Yijun Sun, Jian Li
204
Voted
ICML
2004
IEEE
16 years 7 months ago
Distribution kernels based on moments of counts
Many applications in text and speech processing require the analysis of distributions of variable-length sequences. We recently introduced a general kernel framework, rational ker...
Corinna Cortes, Mehryar Mohri
KDD
2001
ACM
216views Data Mining» more  KDD 2001»
16 years 7 months ago
The distributed boosting algorithm
In this paper, we propose a general framework for distributed boosting intended for efficient integrating specialized classifiers learned over very large and distributed homogeneo...
Aleksandar Lazarevic, Zoran Obradovic
CHI
2008
ACM
16 years 7 months ago
WallCology: designing interaction affordances for learner engagement in authentic science inquiry
The broadening array of technologies available to support the design of classroom activity has the potential to reshape science learning in schools. This paper presents a ubiquito...
Brenda López Silva, Brian Uphoff, Darshan B...
ALT
2000
Springer
16 years 4 months ago
On the Noise Model of Support Vector Machines Regression
Abstract. Support Vector Machines Regression (SVMR) is a learning technique where the goodness of fit is measured not by the usual quadratic loss function (the mean square error),...
Massimiliano Pontil, Sayan Mukherjee, Federico Gir...