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» Dimensionality reduction techniques for proximity problems
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TSP
2008
151views more  TSP 2008»
13 years 7 months ago
Reduce and Boost: Recovering Arbitrary Sets of Jointly Sparse Vectors
The rapid developing area of compressed sensing suggests that a sparse vector lying in a high dimensional space can be accurately and efficiently recovered from only a small set of...
Moshe Mishali, Yonina C. Eldar
ECCV
2008
Springer
14 years 5 months ago
Window Annealing over Square Lattice Markov Random Field
Monte Carlo methods and their subsequent simulated annealing are able to minimize general energy functions. However, the slow convergence of simulated annealing compared with more ...
Ho Yub Jung, Kyoung Mu Lee, Sang Uk Lee
MICCAI
2003
Springer
14 years 8 months ago
Caudate Shape Discrimination in Schizophrenia Using Template-Free Non-parametric Tests
This paper describes shape analysis of the caudate nucleus structure in a large schizophrenia study (30 controls, 60 schizophrenics). Although analysis of the caudate has not drawn...
Y. Sampath K. Vetsa, Martin Styner, Stephen M. Piz...
IROS
2009
IEEE
138views Robotics» more  IROS 2009»
14 years 2 months ago
Using eigenposes for lossless periodic human motion imitation
— Programming a humanoid robot to perform an action that takes the robot’s complex dynamics into account is a challenging problem. Traditional approaches typically require high...
Rawichote Chalodhorn, Rajesh P. N. Rao
ICDM
2008
IEEE
141views Data Mining» more  ICDM 2008»
14 years 1 months ago
Scalable Tensor Decompositions for Multi-aspect Data Mining
Modern applications such as Internet traffic, telecommunication records, and large-scale social networks generate massive amounts of data with multiple aspects and high dimensiona...
Tamara G. Kolda, Jimeng Sun