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ML
2002
ACM
146views Machine Learning» more  ML 2002»
15 years 4 months ago
Kernel Matching Pursuit
Matching Pursuit algorithms learn a function that is a weighted sum of basis functions, by sequentially appending functions to an initially empty basis, to approximate a target fu...
Pascal Vincent, Yoshua Bengio
156
Voted
ML
2010
ACM
159views Machine Learning» more  ML 2010»
15 years 3 months ago
Algorithms for optimal dyadic decision trees
Abstract A dynamic programming algorithm for constructing optimal dyadic decision trees was recently introduced, analyzed, and shown to be very effective for low dimensional data ...
Don R. Hush, Reid B. Porter
151
Voted
ICMLA
2009
15 years 2 months ago
Structured Prediction with Relative Margin
In structured prediction problems, outputs are not confined to binary labels; they are often complex objects such as sequences, trees, or alignments. Support Vector Machine (SVM) ...
Pannagadatta K. Shivaswamy, Tony Jebara
146
Voted
ICMLA
2009
15 years 2 months ago
Ranking Electrical Feeders of the New York Power Grid
components of a system by susceptibility to failure. In this extended abstract, we present an ongoing project to rank the underground primary feeders of Consolidated Edison Company...
Philip Gross, Ansaf Salleb-Aouissi, Haimonti Dutta...
JMLR
2010
211views more  JMLR 2010»
14 years 12 months ago
Minimum Conditional Entropy Clustering: A Discriminative Framework for Clustering
In this paper, we introduce an assumption which makes it possible to extend the learning ability of discriminative model to unsupervised setting. We propose an informationtheoreti...
Bo Dai, Baogang Hu