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» On soft mappings
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ICML
2010
IEEE
13 years 8 months ago
Non-Local Contrastive Objectives
Pseudo-likelihood and contrastive divergence are two well-known examples of contrastive methods. These algorithms trade off the probability of the correct label with the probabili...
David Vickrey, Cliff Chiung-Yu Lin, Daphne Koller
INFFUS
2006
103views more  INFFUS 2006»
13 years 7 months ago
Information fusion approaches to the automatic pronunciation of print by analogy
Automatic pronunciation of words from their spelling alone is a hard computational problem, especially for languages like English and French where there is only a partially consis...
Robert I. Damper, Yannick Marchand
SCHOLARPEDIA
2008
89views more  SCHOLARPEDIA 2008»
13 years 6 months ago
Support vector clustering
We present a novel method for clustering using the support vector machine approach. Data points are mapped to a high dimensional feature space, where support vectors are used to d...
Asa Ben-Hur
ISBI
2011
IEEE
12 years 11 months ago
Interventional MR-imaging for thermal ablation therapy
Magnetic Resonance Imaging (MRI) has several unique advantages for guiding thermal ablation therapies. It not only provides excellent soft-tissue contrast and multiplanar capabili...
Eva Rothgang, Wesley D. Gilson, Wilhelm Strehl, Li...
CVPR
2012
IEEE
11 years 10 months ago
Multiclass pixel labeling with non-local matching constraints
A popular approach to pixel labeling problems, such as multiclass image segmentation, is to construct a pairwise conditional Markov random field (CRF) over image pixels where the...
Stephen Gould