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JMLR
2006
108views more  JMLR 2006»
14 years 9 months ago
Learning Spectral Clustering, With Application To Speech Separation
Spectral clustering refers to a class of techniques which rely on the eigenstructure of a similarity matrix to partition points into disjoint clusters, with points in the same clu...
Francis R. Bach, Michael I. Jordan
SLP
1989
105views more  SLP 1989»
14 years 11 months ago
Automatic Ordering of Subgoals - A Machine Learning Approach
This paper describes a learning system, LASSY1, which explores domains represented by Prolog databases, and use its acquired knowledge to increase the efficiency of a Prolog inter...
Shaul Markovitch, Paul D. Scott
CVPR
2008
IEEE
15 years 12 months ago
Learning and using taxonomies for fast visual categorization
The computational complexity of current visual categorization algorithms scales linearly at best with the number of categories. The goal of classifying simultaneously Ncat = 104 -...
Gregory Griffin, Darya Perona
ICML
2008
IEEE
15 years 10 months ago
Cost-sensitive multi-class classification from probability estimates
For two-class classification, it is common to classify by setting a threshold on class probability estimates, where the threshold is determined by ROC curve analysis. An analog fo...
Deirdre B. O'Brien, Maya R. Gupta, Robert M. Gray
ICML
2008
IEEE
15 years 10 months ago
ManifoldBoost: stagewise function approximation for fully-, semi- and un-supervised learning
We introduce a boosting framework to solve a classification problem with added manifold and ambient regularization costs. It allows for a natural extension of boosting into both s...
Nicolas Loeff, David A. Forsyth, Deepak Ramachandr...