A note on genetic algorithms for large-scale feature selection
Pattern Recognition Letters
Software caching vs. prefetching
Proceedings of the 3rd international symposium on Memory management
The Simple Genetic Algorithm: Foundations and Theory
The Simple Genetic Algorithm: Foundations and Theory
Feature Selection for Knowledge Discovery and Data Mining
Feature Selection for Knowledge Discovery and Data Mining
Comparison of Classifier-Specific Feature Selection Algorithms
Proceedings of the Joint IAPR International Workshops on Advances in Pattern Recognition
Cache Diversity in Genetic Algorithm Design
Proceedings of the Thirteenth International Florida Artificial Intelligence Research Society Conference
Feature Selection in Web Applications By ROC Inflections and Powerset Pruning
SAINT '01 Proceedings of the 2001 Symposium on Applications and the Internet (SAINT 2001)
Feature selection based on rough sets and particle swarm optimization
Pattern Recognition Letters
A Stochastic Algorithm for Feature Selection in Pattern Recognition
The Journal of Machine Learning Research
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IEEE Transactions on Computers
Analysing and improving clustering based sampling for microprocessor simulation
International Journal of High Performance Computing and Networking
Different metaheuristic strategies to solve the feature selection problem
Pattern Recognition Letters
Feature selection using tabu search with long-term memories and probabilistic neural networks
Pattern Recognition Letters
Caching in the TSP Search Space
IEA/AIE '09 Proceedings of the 22nd International Conference on Industrial, Engineering and Other Applications of Applied Intelligent Systems: Next-Generation Applied Intelligence
Optimal time-space tradeoff in probabilistic inference
IJCAI'03 Proceedings of the 18th international joint conference on Artificial intelligence
Two step ant colony system to solve the feature selection problem
CIARP'06 Proceedings of the 11th Iberoamerican conference on Progress in Pattern Recognition, Image Analysis and Applications
Improving the performance of constructive multi-start search using record-keeping
IEA/AIE'12 Proceedings of the 25th international conference on Industrial Engineering and Other Applications of Applied Intelligent Systems: advanced research in applied artificial intelligence
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This paper reports the results of a research effort that explores time/space tradeoffs inherent to genetic algorithms (GA). The study analyzes redundancy in the GA search space and lays out a schema for efficient utilization of record keeping in the form of a cache to minimize redundancy. The application used for evaluation of the record keeping procedure is feature selection for computer workload characterization. The experimental results demonstrate the utility of record keeping in the GA domain, and show a significant reduction in execution time with virtually the same solution quality.