2008-07-09-choi08a.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
Approximating the partition function by deleting and then correcting for model edges	We propose an approach for approximating the partition function which is based on two steps: (1) computing the partition function of a simplified model which is obtained by deleting model edges, and (2) rectifying the result by applying an edge-by-edge correction. The approach leads to an intuitive framework in which one can trade-off the quality of an approximation with the complexity of computing it. It also includes the Bethe free energy approximation as a degenerate case. We develop the approach theoretically in this paper and provide a number of empirical results that reveal its practical utility.	inproceedings	Proceedings of Machine Learning Research	PMLR	2640-3498	choi08a	0	Approximating the partition function by deleting and then correcting for model edges	79	87	79-87	79	false	McAllester, David A. and Myllym{"a}ki, Petri	given family David A. McAllester given family Petri Myllymäki	Choi, Arthur and Darwiche, Adnan	given family Arthur Choi given family Adnan Darwiche	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/choi08a/choi08a.pdf