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» Bayesian inference in estimation of distribution algorithms
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KDD
2012
ACM
201views Data Mining» more  KDD 2012»
11 years 10 months ago
Learning from crowds in the presence of schools of thought
Crowdsourcing has recently become popular among machine learning researchers and social scientists as an effective way to collect large-scale experimental data from distributed w...
Yuandong Tian, Jun Zhu
SPAA
2004
ACM
14 years 1 months ago
Adaptive channel queue routing on k-ary n-cubes
This paper introduces a new adaptive method, Channel Queue Routing (CQR), for load-balanced routing on k-ary n-cube interconnection networks. CQR estimates global congestion in th...
Arjun Singh, William J. Dally, Amit K. Gupta, Bria...
KDD
2009
ACM
203views Data Mining» more  KDD 2009»
14 years 8 months ago
Characterizing individual communication patterns
The increasing availability of electronic communication data, such as that arising from e-mail exchange, presents social and information scientists with new possibilities for char...
R. Dean Malmgren, Jake M. Hofman, Luis A. N. Amara...
GECCO
2007
Springer
192views Optimization» more  GECCO 2007»
14 years 2 months ago
SDR: a better trigger for adaptive variance scaling in normal EDAs
Recently, advances have been made in continuous, normal– distribution–based Estimation–of–Distribution Algorithms (EDAs) by scaling the variance up from the maximum–like...
Peter A. N. Bosman, Jörn Grahl, Franz Rothlau...
ECCV
2002
Springer
14 years 9 months ago
Learning Shape from Defocus
We present a novel method for inferring three-dimensional shape from a collection of defocused images. It is based on the observation that defocused images are the null-space of ce...
Paolo Favaro, Stefano Soatto