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PAKDD
2011
ACM
253views Data Mining» more  PAKDD 2011»
14 years 7 months ago
Balance Support Vector Machines Locally Using the Structural Similarity Kernel
A structural similarity kernel is presented in this paper for SVM learning, especially for learning with imbalanced datasets. Kernels in SVM are usually pairwise, comparing the sim...
Jianxin Wu
CVPR
1996
IEEE
15 years 8 months ago
Sparse Representations for Image Decomposition with Occlusions
We study the problem of how to detect \interesting objects" appeared in a given image, I. Our approach is to treat it as a function approximation problem based on an over-red...
Michael J. Donahue, Davi Geiger, Tyng-Luh Liu, Rob...
ESANN
2008
15 years 5 months ago
Learning Data Representations with Sparse Coding Neural Gas
Abstract. We consider the problem of learning an unknown (overcomplete) basis from an unknown sparse linear combination. Introducing the "sparse coding neural gas" algori...
Kai Labusch, Erhardt Barth, Thomas Martinetz
NIPS
2008
15 years 5 months ago
Sparse Signal Recovery Using Markov Random Fields
Compressive Sensing (CS) combines sampling and compression into a single subNyquist linear measurement process for sparse and compressible signals. In this paper, we extend the th...
Volkan Cevher, Marco F. Duarte, Chinmay Hegde, Ric...
TSP
2008
124views more  TSP 2008»
15 years 4 months ago
Dictionary Preconditioning for Greedy Algorithms
This article introduces the concept of sensing dictionaries. It presents an alteration of greedy algorithms like thresholding or (Orthogonal) Matching Pursuit which improves their...
Karin Schnass, Pierre Vandergheynst