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GECCO
2006
Springer
192views Optimization» more  GECCO 2006»
13 years 11 months ago
Optimising cancer chemotherapy using an estimation of distribution algorithm and genetic algorithms
This paper presents a methodology for using heuristic search methods to optimise cancer chemotherapy. Specifically, two evolutionary algorithms - Population Based Incremental Lear...
Andrei Petrovski, Siddhartha Shakya, John A. W. Mc...
ICASSP
2011
IEEE
12 years 11 months ago
Learning non-parametric models of pronunciation
As more data becomes available for a given speech recognition task, the natural way to improve recognition accuracy is to train larger models. But, while this strategy yields mode...
Brian Hutchinson, Jasha Droppo
DAC
2005
ACM
14 years 8 months ago
Structural search for RTL with predicate learning
We present an efficient search strategy for satisfiability checking on circuits represented at the register-transfer-level (RTL). We use the RTL circuit structure by extending con...
Ganapathy Parthasarathy, Madhu K. Iyer, Kwang-Ting...
FLAIRS
2007
13 years 9 months ago
Learning to Identify Global Bottlenecks in Constraint Satisfaction Search
Using information from failures to guide subsequent search is an important technique for solving combinatorial problems in domains such as boolean satisfiability (SAT) and constr...
Diarmuid Grimes, Richard J. Wallace
GECCO
2006
Springer
179views Optimization» more  GECCO 2006»
13 years 11 months ago
Parisian evolution with honeybees for three-dimensional reconstruction
This paper introduces a novel analogy with the way in which honeybee colonies operate in order to solve the problem of sparse and quasi dense reconstruction. To successfully solve...
Gustavo Olague, Cesar Puente