2008-07-09-streeter08a.md

title	abstract	layout	series	publisher	issn	id	month	tex_title	firstpage	lastpage	page	order	cycles	bibtex_editor	editor	bibtex_author	author	date	note	address	container-title	volume	genre	issued	pdf	extras
New techniques for algorithm portfolio design	We present and evaluate new techniques for designing algorithm portfolios. In our view, the problem has both a scheduling aspect and a machine learning aspect. Prior work has largely addressed one of the two aspects in isolation. Building on recent work on the scheduling aspect of the problem, we present a technique that addresses both aspects simultaneously and has attractive theoretical guarantees. Experimentally, we show that this technique can be used to improve the performance of state-of-the-art algorithms for Boolean satisfiability, zero-one integer programming, and A.I. planning.	inproceedings	Proceedings of Machine Learning Research	PMLR	2640-3498	streeter08a	0	New techniques for algorithm portfolio design	519	527	519-527	519	false	McAllester, David A. and Myllym{"a}ki, Petri	given family David A. McAllester given family Petri Myllymäki	Streeter, Matthew and Smith, Stephen F.	given family Matthew Streeter given family Stephen F. Smith	2008-07-09	Reissued by PMLR on 30 October 2024.		Proceedings of the 24th Conference on Uncertainty in Artificial Intelligence	R6	inproceedings	date-parts 2008 7 9	http://proceedings.mlr.press/r6/streeter08a/streeter08a.pdf