Solving inverse problems using an EM approach to density estimation

Solving inverse problems using an EM approach to density estimation (1993)

by Zoubin Ghahramani

Venue:	Proceedings of the 1993 Connectionist Models Summer School
Citations:	13 - 2 self

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Datum	Value	Source
TITLE	Solving inverse problems using an EM approach to density estimation	SVM HeaderParse 0.1
AUTHOR NAME	Zoubin Ghahramani	SVM HeaderParse 0.1
AUTHOR AFFIL	1; Department of Brain & Cognitive Sciences; Massachusetts Institute of Technology	SVM HeaderParse 0.2
AUTHOR ADDR	Cambridge, MA 02139	SVM HeaderParse 0.1
ABSTRACT	This paper proposes density estimation as a feasible approach to the wide class of learning problems where traditional function approximation methods fail. These problems generally involve learning the inverse of causal systems, specifically when the inverse is a non-convex mapping. We demonstrate the approach through three case studies: the inverse kinematics of a three-joint planar arm, the acoustics of a four-tube articulatory model, and the localization of multiple objects from sensor data. The learning algorithm presented differs from regression-based algorithms in that no distinction is made between input and output variables; the joint density is estimated via the EM algorithm and can be used to represent any input/output map by forming the conditional density of the output given the input.	user correction - Legacy Corrections
YEAR	1993	user correction - Legacy Corrections
VENUE	Proceedings of the 1993 Connectionist Models Summer School	INFERENCE
VENUE TYPE	CONFERENCE	INFERENCE
PAGES	316--323	INFERENCE
CITATIONS	17 found	ParsCit 1.0