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169
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NIPS
1992
15 years 5 months ago
Hidden Markov Model} Induction by Bayesian Model Merging
This paper describes a technique for learning both the number of states and the topologyof Hidden Markov Models from examples. The inductionprocess starts with the most specific m...
Andreas Stolcke, Stephen M. Omohundro
VMV
2007
122views Visualization» more  VMV 2007»
15 years 5 months ago
An iterative framework for registration with reconstruction
The core of most registration algorithms aligns scan data by pairs, minimizing their relative distance. This local optimization must generally pass through a validation procedure t...
Thales Vieira, Adelailson Peixoto, Luiz Velho, Tho...
GECCO
2008
Springer
157views Optimization» more  GECCO 2008»
15 years 5 months ago
Self-adaptive mutation rates in genetic algorithm for inverse design of cellular automata
Self-adaptation is used a lot in Evolutionary Strategies and with great success, yet for some reason it is not the mutation adaptation of choice for Genetic Algorithms. This poste...
Ron Breukelaar, Thomas Bäck
137
Voted
ICFP
2010
ACM
15 years 5 months ago
Fortifying macros
Existing macro systems force programmers to make a choice between clarity of specification and robustness. If they choose clarity, they must forgo validating significant parts of ...
Ryan Culpepper, Matthias Felleisen
CEC
2007
IEEE
15 years 4 months ago
Designing memetic algorithms for real-world applications using self-imposed constraints
— Memetic algorithms (MAs) combine the global exploration abilities of evolutionary algorithms with a local search to further improve the solutions. While a neighborhood can be e...
Thomas Michelitsch, Tobias Wagner, Dirk Biermann, ...