Nonuniform Dynamic Discretization in Hybrid Networks

Nonuniform Dynamic Discretization in Hybrid Networks (1997)

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by Alexander Kozlov , Daphne Koller

Venue:	In Proc. UAI
Citations:	47 - 3 self

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Datum	Value	Source
TITLE	Nonuniform Dynamic Discretization in Hybrid Networks	user correction - Legacy Corrections
AUTHOR NAME	Alexander Kozlov	user correction - Legacy Corrections
AUTHOR AFFIL	Department of Computer Science; Stanford University	user correction - Legacy Corrections
AUTHOR ADDR	Stanford, CA 94305-9010	user correction - Legacy Corrections
AUTHOR NAME	Daphne Koller	user correction - Legacy Corrections
AUTHOR AFFIL	Department of Computer Science; Stanford University	user correction - Legacy Corrections
AUTHOR ADDR	Stanford, CA 94305-9010	user correction - Legacy Corrections
ABSTRACT	We consider probabilistic inference in general hybrid networks, which include continuous and discrete variables in an arbitrary topology. We reexamine the question of variable discretization in a hybrid network aiming at minimizing the information loss induced by the discretization. We show that a nonuniform partition across all variables as opposed to uniform partition of each variable separately reduces the size of the data structures needed to represent a continuous function. We also provide a simple but efficient procedure for nonuniform partition. To represent a nonuniform discretization in the computer memory, we introduce a new data structure, which we call a Binary Split Partition (BSP) tree. We show that BSP trees can be an exponential factor smaller than the data structures in the standard uniform discretization in multiple dimensions and show how the BSP trees can be used in the standard join tree algorithm. We show that the accuracy of the inference process can be significa...	user correction - Legacy Corrections
YEAR	1997	INFERENCE
VENUE	In Proc. UAI	INFERENCE
VENUE TYPE	CONFERENCE	INFERENCE
PAGES	314--325	INFERENCE
VOLUME	13	INFERENCE
CITATIONS	13 found	ParsCit 1.0