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CIKM
1999
Springer
13 years 10 months ago
Training a Selection Function for Extraction
In this paper we compare performance of several heuristics in generating informative generic/query-oriented extracts for newspaper articles in order to learn how topic prominence ...
Chin-Yew Lin
CLOUDCOM
2010
Springer
13 years 4 months ago
Scaling Populations of a Genetic Algorithm for Job Shop Scheduling Problems Using MapReduce
Inspired by Darwinian evolution, a genetic algorithm (GA) approach is one of the popular heuristic methods for solving hard problems, such as the Job Shop Scheduling Problem (JSSP...
Di-Wei Huang, Jimmy Lin
WSC
2008
13 years 8 months ago
Creating and using non-kinetic effects: Training joint forces for asymmetric operations
US military forces now face asymmetric military operations. Management of relationships with civilians is often crucial to success. Local population groups can provide critical in...
Hugh Henry, Robert G. Chamberlain
GECCO
2003
Springer
13 years 11 months ago
A Kernighan-Lin Local Improvement Heuristic That Solves Some Hard Problems in Genetic Algorithms
We present a Kernighan-Lin style local improvement heuristic for genetic algorithms. We analyze the run-time cost of the heuristic. We demonstrate through experiments that the heur...
William A. Greene
NPL
2006
109views more  NPL 2006»
13 years 6 months ago
CB3: An Adaptive Error Function for Backpropagation Training
Effective backpropagation training of multi-layer perceptrons depends on the incorporation of an appropriate error or objective function. Classification-based (CB) error functions ...
Michael Rimer, Tony Martinez