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CORR
2008
Springer
118views Education» more  CORR 2008»
14 years 12 months ago
Learning Low-Density Separators
Abstract. We define a novel, basic, unsupervised learning problem learning the the lowest density homogeneous hyperplane separator of an unknown probability distribution. This task...
Shai Ben-David, Tyler Lu, Dávid Pál,...
TSP
2008
103views more  TSP 2008»
14 years 11 months ago
Low-Rank Variance Approximation in GMRF Models: Single and Multiscale Approaches
Abstract--We present a versatile framework for tractable computation of approximate variances in large-scale Gaussian Markov random field estimation problems. In addition to its ef...
Dmitry M. Malioutov, Jason K. Johnson, Myung Jin C...
CORR
2010
Springer
94views Education» more  CORR 2010»
14 years 9 months ago
The Stability of Low-Rank Matrix Reconstruction: a Constrained Singular Value View
The stability of low-rank matrix reconstruction is investigated in this paper. The -constrained minimal singular value ( -CMSV) of the measurement operator is shown to determine t...
Gongguo Tang, Arye Nehorai
ISSTA
2006
ACM
15 years 5 months ago
Path-oriented random testing
Test campaigns usually require only a restricted subset of paths in a program to be thoroughly tested. As random testing (RT) offers interesting fault-detection capacities at low ...
Arnaud Gotlieb, Matthieu Petit
ISPA
2007
Springer
15 years 6 months ago
Binomial Graph: A Scalable and Fault-Tolerant Logical Network Topology
The number of processors embedded in high performance computing platforms is growing daily to solve larger and more complex problems. The logical network topologies must also suppo...
Thara Angskun, George Bosilca, Jack Dongarra