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» Learning a Classification Model for Segmentation
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ISMB
1993
15 years 6 months ago
Representation for Discovery of Protein Motifs
There are several dimensions and levels of complexity in which information on protein motifs may be available. For example, onedimensional sequence motifs may be associated with s...
Darrell Conklin, Suzanne Fortier, Janice I. Glasgo...
EMNLP
2008
15 years 6 months ago
Understanding the Value of Features for Coreference Resolution
In recent years there has been substantial work on the important problem of coreference resolution, most of which has concentrated on the development of new models and algorithmic...
Eric Bengtson, Dan Roth
ICCV
2009
IEEE
1318views Computer Vision» more  ICCV 2009»
16 years 9 months ago
Non-Local Sparse Models for Image Restoration
We propose in this paper to unify two different ap- proaches to image restoration: On the one hand, learning a basis set (dictionary) adapted to sparse signal descriptions has p...
Julien Mairal, Francis Bach, Jean Ponce, Guillermo...
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ICML
2007
IEEE
16 years 5 months ago
Local similarity discriminant analysis
We propose a local, generative model for similarity-based classification. The method is applicable to the case that only pairwise similarities between samples are available. The c...
Luca Cazzanti, Maya R. Gupta
ICML
2003
IEEE
16 years 5 months ago
Regression Error Characteristic Curves
Receiver Operating Characteristic (ROC) curves provide a powerful tool for visualizing and comparing classification results. Regression Error Characteristic (REC) curves generaliz...
Jinbo Bi, Kristin P. Bennett