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» Solving iterated functions using genetic programming
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CVPR
2006
IEEE
14 years 9 months ago
Solving Markov Random Fields using Second Order Cone Programming Relaxations
This paper presents a generic method for solving Markov random fields (MRF) by formulating the problem of MAP estimation as 0-1 quadratic programming (QP). Though in general solvi...
M. Pawan Kumar, Philip H. S. Torr, Andrew Zisserma...
IPPS
2002
IEEE
14 years 10 days ago
A High Performance Algorithm for Incompressible Flows Using Local Solenoidal Functions
The convergence of iterative methods used to solve the linear systems arising in incompressible flow problems is sensitive to flow parameters such as the Reynolds number, time s...
Sreekanth R. Sambavaram, Vivek Sarin
BMCBI
2006
175views more  BMCBI 2006»
13 years 7 months ago
Parameter estimation for stiff equations of biosystems using radial basis function networks
Background: The modeling of dynamic systems requires estimating kinetic parameters from experimentally measured time-courses. Conventional global optimization methods used for par...
Yoshiya Matsubara, Shinichi Kikuchi, Masahiro Sugi...
GECCO
2007
Springer
177views Optimization» more  GECCO 2007»
14 years 1 months ago
Evolving problem heuristics with on-line ACGP
Genetic Programming uses trees to represent chromosomes. The user defines the representation space by defining the set of functions and terminals to label the nodes in the trees. ...
Cezary Z. Janikow
ITICSE
1997
ACM
13 years 11 months ago
A genetic algorithms tutorial tool for numerical function optimisation
The field of Genetic Algorithms has grown into a huge area over the last few years. Genetic Algorithms are adaptive methods, which can be used to solve search and optimisation pro...
Edmund K. Burke, D. B. Varley