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» Formalization of Continuous Probability Distributions
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JMLR
2010
202views more  JMLR 2010»
13 years 4 months ago
Learning the Structure of Deep Sparse Graphical Models
Deep belief networks are a powerful way to model complex probability distributions. However, it is difficult to learn the structure of a belief network, particularly one with hidd...
Ryan Prescott Adams, Hanna M. Wallach, Zoubin Ghah...
JMLR
2012
12 years 16 days ago
Low rank continuous-space graphical models
Constructing tractable dependent probability distributions over structured continuous random vectors is a central problem in statistics and machine learning. It has proven diffic...
Carl Smith, Frank Wood, Liam Paninski
IPPS
2005
IEEE
14 years 3 months ago
Dynamic RWA Based on the Combination of Mobile Agents Technique and Genetic Algorithm in WDM Networks with Sparse Wavelength Con
In this paper, we study the dynamic RWA problem in WDM networks with sparse wavelength conversion and propose a novel hybrid algorithm for it based on the combination of mobile ag...
Vinh Trong Le, Xiaohong Jiang, Son-Hong Ngo, Susum...
CCGRID
2004
IEEE
14 years 1 months ago
Supporting quality of service in a non-dedicated opportunistic environment
In this paper we investigate the utilization of nondedicated, opportunistic resources in a desktop environment to provide statistical assurances to a class of QoS sensitive, soft ...
Jin Liang, Klara Nahrstedt
APPML
2007
154views more  APPML 2007»
13 years 10 months ago
Comparison of distances between measures
The problem of optimal transportation between a set of sources and a set of wells has become recently the object of new mathematical models generalizing the Monge-Kantorovich prob...
Jean-Michel Morel, Filippo Santambrogio