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Meta-learning and Algorithm Selection
Proceedings of the International Workshop on Meta-learning and Algorithm Selection
co-located with 21st European Conference on Artificial Intelligence (ECAI 2014)
Prague, Czech Republic, August 19, 2014.
Joaquin Vanschoren, Eindhoven University of Technology, The Netherlands
Pavel Brazdil, University of Porto, Portugal
Carlos Soares, University of Porto, Portugal
Lars Kotthoff, University College Cork, Ireland
Table of Contents
Invited Talk Abstracts
- Using Meta-Learning to Initialize Bayesian Optimization of Hyperparameters3-10
Matthias Feurer, Tobias Springenberg, Frank Hutter
- Similarity Measures of Algorithm Performance for Cost-Sensitive Scenarios11-17
Carlos Eduardo Castor de Melo, Ricardo Prudêncio
- Using Metalearning to Predict When Parameter Optimization Is Likely to Improve Classification
Parker Ridd, Christophe Giraud-Carrier
- Surrogate Benchmarks for Hyperparameter Optimization24-31
Katharina Eggensperger, Frank Hutter, Holger Hoos, Kevin Leyton-Brown
- A Framework To Decompose And Develop Metafeatures32-36
Fabio Pinto, Carlos Soares, Joao Mendes-Moreira
- Towards Meta-learning over Data Streams37-38
Jan van Rijn, Geoffrey Holmes, Bernhard Pfahringer, Joaquin Vanschoren
- Recommending Learning Algorithms and Their Associated Hyperparameters39-40
Michael Smith, Logan Mitchell, Christophe Giraud-Carrier, Tony Martinez
- An Easy to Use Repository for Comparing and Improving Machine Learning Algorithm Usage41-48
Michael Smith, Andrew White, Christophe Giraud-Carrier, Tony Martinez
- Measures for Combining Accuracy and Time for Meta-learning49-50
Salisu Abdulrahman, Pavel Brazdil
The whole proceedings can also be downloaded as a single file (PDF).
We offer a BibTeX file for citing papers of this workshop from LaTeX.
2014-08-02: submitted by Joaquin Vanschoren
2014-08-03: published on CEUR-WS.org