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» Locally Competitive Algorithms for Sparse Approximation
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SAT
2010
Springer
172views Hardware» more  SAT 2010»
13 years 5 months ago
On the Relative Merits of Simple Local Search Methods for the MAX-SAT Problem
Algorithms based on local search are popular for solving many optimization problems including the maximum satisfiability problem (MAXSAT). With regard to MAXSAT, the state of the ...
Denis Pankratov, Allan Borodin
TMC
2010
224views more  TMC 2010»
13 years 5 months ago
Multihop Range-Free Localization in Anisotropic Wireless Sensor Networks: A Pattern-Driven Scheme
—This paper focuses on multihop range-free localization in anisotropic wireless sensor networks. In anisotropic networks, geometric distance between a pair of sensor nodes is not...
Qingjun Xiao, Bin Xiao, Jiannong Cao, Jianping Wan...
UAI
2003
13 years 8 months ago
Systematic vs. Non-systematic Algorithms for Solving the MPE Task
The paper explores the power of two systematic Branch and Bound search algorithms that exploit partition-based heuristics, BBBT (a new algorithm for which the heuristic informatio...
Radu Marinescu 0002, Kalev Kask, Rina Dechter
VLSISP
2010
254views more  VLSISP 2010»
13 years 5 months ago
Manifold Based Local Classifiers: Linear and Nonlinear Approaches
Abstract In case of insufficient data samples in highdimensional classification problems, sparse scatters of samples tend to have many ‘holes’—regions that have few or no nea...
Hakan Cevikalp, Diane Larlus, Marian Neamtu, Bill ...
NN
1998
Springer
177views Neural Networks» more  NN 1998»
13 years 7 months ago
Soft vector quantization and the EM algorithm
The relation between hard c-means (HCM), fuzzy c-means (FCM), fuzzy learning vector quantization (FLVQ), soft competition scheme (SCS) of Yair et al. (1992) and probabilistic Gaus...
Ethem Alpaydin