56 search results - page 5 / 12 » Stochastic methods for l1 regularized loss minimization |
109
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JSCIC
2010
14 years 7 months ago
2010
Variational models for image segmentation have many applications, but can be slow to compute. Recently, globally convex segmentation models have been introduced which are very rel...
JMIV
2006
15 years 10 days ago
2006
Abstract. A generalized iterative regularization procedure based on the total variation penalization is introduced for image denoising models with non-quadratic convex fidelity ter...
109
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ECIR
2010
Springer
14 years 10 months ago
2010
Springer
Abstract. Machine learning ranking methods are increasingly applied to ranking tasks in information retrieval (IR). However ranking tasks in IR often differ from standard ranking t...
114
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ICML
2010
IEEE
15 years 1 months ago
2010
IEEE
Many structured prediction tasks involve complex models where inference is computationally intractable, but where it can be well approximated using a linear programming relaxation...
ECCV
2008
Springer
16 years 2 months ago
2008
Springer
Abstract. We present a technique for learning the parameters of a continuousstate Markov random field (MRF) model of optical flow, by minimizing the training loss for a set of grou...