2008-07-09-choi08a.md

abstract	title	year	layout	series	publisher	issn	id	month	tex_title	firstpage	lastpage	page	order	cycles	bibtex_author	author	date	note	address	container-title	volume	genre	issued	pdf	extras
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.	Approximating the partition function by deleting and then correcting for model edges	2008	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	Choi, Arthur and Darwiche, Adnan	given family Arthur Choi given family Adnan Darwiche	2008-07-09	Reissued by PMLR on 09 October 2024.		Proceedings of the 24th Conference on Uncertainty in Artificial Intelligence	R6	inproceedings	date-parts 2008 7 9	https://raw.githubusercontent.com/mlresearch/r6/main/assets/choi08a/choi08a.pdf