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» Stochastic methods for l1 regularized loss minimization
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ICPR
2008
IEEE
14 years 6 months ago
Bregman distance to L1 regularized logistic regression
In this work we investigate the relationship between Bregman distances and regularized Logistic Regression model. We present a detailed study of Bregman Distance minimization, a f...
Mithun Das Gupta, Thomas S. Huang
ICML
2007
IEEE
14 years 6 months ago
Scalable training of L1-regularized log-linear models
The l-bfgs limited-memory quasi-Newton method is the algorithm of choice for optimizing the parameters of large-scale log-linear models with L2 regularization, but it cannot be us...
Galen Andrew, Jianfeng Gao
ICASSP
2009
IEEE
14 years 1 days ago
L1 regularized super-resolution from unregistered omnidirectional images
In this paper, we address the problem of super-resolution from multiple low-resolution omnidirectional images with inexact registration. Such a problem is typically encountered in...
Zafer Arican, Pascal Frossard
ECCV
2004
Springer
14 years 7 months ago
A l1-Unified Variational Framework for Image Restoration
Among image restoration literature, there are mainly two kinds of approach. One is based on a process over image wavelet coefficients, as wavelet shrinkage for denoising. The other...
Julien Bect, Laure Blanc-Féraud, Gilles Aub...
ICCV
2009
IEEE
1957views Computer Vision» more  ICCV 2009»
14 years 10 months ago
Robust Visual Tracking using L1 Minimization
In this paper we propose a robust visual tracking method by casting tracking as a sparse approximation problem in a particle filter framework. In this framework, occlusion, corru...
Xue Mei, Haibin Ling