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NPL
1998
133views more  NPL 1998»
13 years 7 months ago
Parallel Coarse Grain Computing of Boltzmann Machines
Abstract. The resolution of combinatorial optimization problems can greatly benefit from the parallel and distributed processing which is characteristic of neural network paradigm...
Julio Ortega, Ignacio Rojas, Antonio F. Día...
BMCBI
2008
137views more  BMCBI 2008»
13 years 7 months ago
A dynamic Bayesian network approach to protein secondary structure prediction
Background: Protein secondary structure prediction method based on probabilistic models such as hidden Markov model (HMM) appeals to many because it provides meaningful informatio...
Xin-Qiu Yao, Huaiqiu Zhu, Zhen-Su She
CMOT
1999
143views more  CMOT 1999»
13 years 7 months ago
Structural Learning: Attraction and Conformity in Task-Oriented Groups
This study extends previous research that showed how informal social sanctions can backfire when members prefer friendship over enforcement of group norms. We use a type of neural...
James A. Kitts, Michael W. Macy, Andreas Flache
COMPUTER
2002
129views more  COMPUTER 2002»
13 years 7 months ago
Networks on Chips: A New SoC Paradigm
of abstraction and coarse granularity and distributed communication control. Focusing on using probabilistic metrics such as average values or variance to quantify design objective...
Luca Benini, Giovanni De Micheli
ICIC
2007
Springer
14 years 1 months ago
Evolutionary Ensemble for In Silico Prediction of Ames Test Mutagenicity
Driven by new regulations and animal welfare, the need to develop in silico models has increased recently as alternative approaches to safety assessment of chemicals without animal...
Huanhuan Chen, Xin Yao