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CVPR
2007
IEEE
14 years 9 months ago
Element Rearrangement for Tensor-Based Subspace Learning
The success of tensor-based subspace learning depends heavily on reducing correlations along the column vectors of the mode-k flattened matrix. In this work, we study the problem ...
Shuicheng Yan, Dong Xu, Stephen Lin, Thomas S. Hua...
CORR
2010
Springer
93views Education» more  CORR 2010»
13 years 7 months ago
Rank Awareness in Joint Sparse Recovery
In this paper we revisit the sparse multiple measurement vector (MMV) problem, where the aim is to recover a set of jointly sparse multichannel vectors from incomplete measurement...
Mike E. Davies, Yonina C. Eldar
CGI
2009
IEEE
13 years 11 months ago
Easy integral surfaces: a fast, quad-based stream and path surface algorithm
Despite the clear benefits that stream and path surfaces bring when visualizing 3D vector fields, their use in both industry and for research has not proliferated. This is due, in...
Tony McLoughlin, Robert S. Laramee, Eugene Zhang
ESANN
2008
13 years 8 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
ICML
2010
IEEE
13 years 8 months ago
Boosting Classifiers with Tightened L0-Relaxation Penalties
We propose a novel boosting algorithm which improves on current algorithms for weighted voting classification by striking a better balance between classification accuracy and the ...
Noam Goldberg, Jonathan Eckstein