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» Sparse Additive Machine
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CVPR
2010
IEEE
15 years 4 months ago
Local Features Are Not Lonely - Laplacian Sparse Coding for Image Classification
Sparse coding which encodes the original signal in a sparse signal space, has shown its state-of-the-art performance in the visual codebook generation and feature quantization pro...
Shenghua Gao, Wai-Hung Tsang, Liang-Tien Chia, Pei...
71
Voted
CORR
2010
Springer
136views Education» more  CORR 2010»
15 years 17 days ago
Optimally Sparse Frames
Frames have established themselves as a means to derive redundant, yet stable decompositions of a signal for analysis or transmission, while also promoting sparse expansions. Howe...
Peter G. Casazza, Andreas Heinecke, Felix Krahmer,...
IJCNN
2006
IEEE
15 years 6 months ago
Pattern Selection for Support Vector Regression based on Sparseness and Variability
— Support Vector Machine has been well received in machine learning community with its theoretical as well as practical value. However, since its training time complexity is cubi...
Jiyoung Sun, Sungzoon Cho
72
Voted
ICML
2009
IEEE
16 years 1 months ago
Gradient descent with sparsification: an iterative algorithm for sparse recovery with restricted isometry property
We present an algorithm for finding an ssparse vector x that minimizes the squareerror y - x 2 where satisfies the restricted isometry property (RIP), with isometric constant 2s ...
Rahul Garg, Rohit Khandekar
ECML
2007
Springer
15 years 6 months ago
Bayesian Inference for Sparse Generalized Linear Models
We present a framework for efficient, accurate approximate Bayesian inference in generalized linear models (GLMs), based on the expectation propagation (EP) technique. The paramete...
Matthias Seeger, Sebastian Gerwinn, Matthias Bethg...