Journal article

Cross-Disciplinary Perspectives on Meta-Learning for Algorithm Selection

Kate A Smith-Miles

ACM Computing Surveys | ASSOC COMPUTING MACHINERY | Published : 2008

DOI: 10.1145/1456650.1456656

University of Melbourne Researchers

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Keywords

Empirical Hardness
Constraint Satisfaction
Science & Technology
Meta-Learning
Performance
Complexity
Algorithms
Optimization
Computer Science, Theory & Methods
Technology
Accuracy
Dataset Characterization
Time
Computer Science
Instances
Sorting
Classification
Model Selection
Forecasting
Algorithm Selection
Landscape Analysis
Combinatorial Optimization
Hardness