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» Using Genetic Algorithms for Solving Hard Problems in GIS
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CORR
2012
Springer
170views Education» more  CORR 2012»
12 years 4 months ago
What Cannot be Learned with Bethe Approximations
We address the problem of learning the parameters in graphical models when inference is intractable. A common strategy in this case is to replace the partition function with its B...
Uri Heinemann, Amir Globerson
RECOMB
2004
Springer
14 years 8 months ago
Computational identification of evolutionarily conserved exons
Phylogenetic hidden Markov models (phylo-HMMs) have recently been proposed as a means for addressing a multispecies version of the ab initio gene prediction problem. These models ...
Adam C. Siepel, David Haussler
HPCS
2005
IEEE
14 years 2 months ago
A Lightweight, Scalable Grid Computing Framework for Parallel Bioinformatics Applications
Abstract— In recent years our society has witnessed an unprecedented growth in computing power available to tackle important problems in science, engineering and medicine. For ex...
Hans De Sterck, Rob S. Markel, Rob Knight
GECCO
2004
Springer
125views Optimization» more  GECCO 2004»
14 years 1 months ago
An Island-Based GA Implementation for VLSI Standard-Cell Placement
Genetic algorithms require relatively large computation time to solve optimization problems, especially in VLSI CAD such as module placement. Therefore, island-based parallel GAs a...
Guangfa Lu, Shawki Areibi
IJON
2010
199views more  IJON 2010»
13 years 5 months ago
DFS-generated pathways in GA crossover for protein structure prediction
Genetic Algorithms (GAs), as nondeterministic conformational search techniques, are promising for solving protein structure prediction (PSP) problems. The crossover operator of a ...
Tamjidul Hoque, Madhu Chetty, Andrew Lewis, Abdul ...