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TSP
2008
143views more  TSP 2008»
15 years 13 days ago
Sparse Representation in Structured Dictionaries With Application to Synthetic Aperture Radar
Sparse signal representations and approximations from overcomplete dictionaries have become an invaluable tool recently. In this paper, we develop a new, heuristic, graph-structure...
Kush R. Varshney, Müjdat Çetin, John W...
113
Voted
CVPR
2011
IEEE
14 years 4 months ago
A Non-convex Relaxation Approach to Sparse Dictionary Learning
Dictionary learning is a challenging theme in computer vision. The basic goal is to learn a sparse representation from an overcomplete basis set. Most existing approaches employ a...
Jianping Shi, Xiang Ren, Jingdong Wang, Guang Dai,...
103
Voted
ICA
2004
Springer
15 years 6 months ago
Postnonlinear Overcomplete Blind Source Separation Using Sparse Sources
Abstract. We present an approach for blindly decomposing an observed random vector x into f(As) where f is a diagonal function i.e. f = f1 × . . . × fm with one-dimensional funct...
Fabian J. Theis, Shun-ichi Amari
106
Voted
MLDM
2007
Springer
15 years 6 months ago
Nonlinear Feature Selection by Relevance Feature Vector Machine
Support vector machine (SVM) has received much attention in feature selection recently because of its ability to incorporate kernels to discover nonlinear dependencies between feat...
Haibin Cheng, Haifeng Chen, Guofei Jiang, Kenji Yo...
SIGIR
2003
ACM
15 years 5 months ago
Question classification using support vector machines
Question classification is very important for question answering. This paper presents our research work on automatic question classification through machine learning approaches. W...
Dell Zhang, Wee Sun Lee