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» On the Use of Restrictions for Learning Bayesian Networks
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NIPS
2007
13 years 8 months ago
A neural network implementing optimal state estimation based on dynamic spike train decoding
It is becoming increasingly evident that organisms acting in uncertain dynamical environments often employ exact or approximate Bayesian statistical calculations in order to conti...
Omer Bobrowski, Ron Meir, Shy Shoham, Yonina C. El...
ESANN
2006
13 years 8 months ago
Non-linear gating network for the large scale classification model CombNET-II
The linear gating classifier (stem network) of the large scale model CombNET-II has been always the limiting factor which restricts the number of the expert classifiers (branch net...
Mauricio Kugler, Toshiyuki Miyatani, Susumu Kuroya...
CP
2003
Springer
14 years 19 days ago
Semi-automatic Modeling by Constraint Acquisition
Constraint programming is a technology which is now widely used to solve combinatorial problems in industrial applications. However, using it requires considerable knowledge and e...
Remi Coletta, Christian Bessière, Barry O'S...
GLOBECOM
2009
IEEE
13 years 11 months ago
Exploring Simulated Annealing and Graphical Models for Optimization in Cognitive Wireless Networks
In this paper we discuss the design of optimization algorithms for cognitive wireless networks (CWNs). Maximizing the perceived network performance towards applications by selectin...
Elena Meshkova, Janne Riihijärvi, Andreas Ach...
CORR
2004
Springer
133views Education» more  CORR 2004»
13 years 7 months ago
Information theory, multivariate dependence, and genetic network inference
We define the concept of dependence among multiple variables using maximum entropy techniques and introduce a graphical notation to denote the dependencies. Direct inference of in...
Ilya Nemenman