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» Estimating random variables from random sparse observations
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IJCNN
2006
IEEE
14 years 1 months ago
Learning to Segment Any Random Vector
— We propose a method that takes observations of a random vector as input, and learns to segment each observation into two disjoint parts. We show how to use the internal coheren...
Aapo Hyvärinen, Jukka Perkiö
FCT
2009
Springer
14 years 2 months ago
On Random Betweenness Constraints
Despite of their applicability betweennness constraints have (to the author’s knowledge) hardly been considered from the random structures point of view. They are essentially di...
Andreas Goerdt
ECSQARU
2005
Springer
14 years 1 months ago
Consonant Random Sets: Structure and Properties
In this paper, we investigate consonant random sets from the point of view of lattice theory. We introduce a new definition of consonancy and study its relationship with possibili...
Enrique Miranda
ISLPED
2009
ACM
100views Hardware» more  ISLPED 2009»
14 years 2 months ago
Tuning-friendly body bias clustering for compensating random variability in subthreshold circuits
Post-fabrication tuning for mitigating manufacturing variability is receiving a significant attention. To reduce leakage increase involved in performance compensation by body bia...
Koichi Hamamoto, Masanori Hashimoto, Yukio Mitsuya...
CORR
2010
Springer
116views Education» more  CORR 2010»
13 years 7 months ago
Estimation with Random Linear Mixing, Belief Propagation and Compressed Sensing
Abstract--We apply Guo and Wang's relaxed belief propagation (BP) method to the estimation of a random vector from linear measurements followed by a componentwise probabilisti...
Sundeep Rangan