ML Anthology

Algorithm Portfolios Based on Cost-Sensitive Hierarchical Clustering

Yuri Malitsky, Ashish Sabharwal, Horst Samulowitz, Meinolf Sellmann
IJCAI 2013 pp. 608-614
/ijcai/2013/malitsky2013ijcai-algorithm/

Abstract

Different solution approaches for combinatorial problems often exhibit incomparable performance that depends on the concrete problem instance to be solved. Algorithm portfolios aim to combine the strengths of multiple algorithmic approaches by training a classifier that selects or schedules solvers dependent on the given instance. We devise a new classifier that selects solvers based on a cost-sensitive hierarchical clustering model. Experimental results on SAT and MaxSAT show that the new method outperforms the most effective portfolio builders to date.

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Cite

Text

Malitsky et al. "Algorithm Portfolios Based on Cost-Sensitive Hierarchical Clustering." International Joint Conference on Artificial Intelligence, 2013.

Markdown

[Malitsky et al. "Algorithm Portfolios Based on Cost-Sensitive Hierarchical Clustering." International Joint Conference on Artificial Intelligence, 2013.](https://mlanthology.org/ijcai/2013/malitsky2013ijcai-algorithm/)

BibTeX

@inproceedings{malitsky2013ijcai-algorithm,
  title     = {{Algorithm Portfolios Based on Cost-Sensitive Hierarchical Clustering}},
  author    = {Malitsky, Yuri and Sabharwal, Ashish and Samulowitz, Horst and Sellmann, Meinolf},
  booktitle = {International Joint Conference on Artificial Intelligence},
  year      = {2013},
  pages     = {608-614},
  url       = {https://mlanthology.org/ijcai/2013/malitsky2013ijcai-algorithm/}
}