MAP Estimation for Graphical Models by Likelihood Maximization

MAP Estimation for Graphical Models by Likelihood Maximization

Computing a maximum a posteriori (MAP) assignment in graphical models is a crucial inference problem for many practical applications. Several provably convergent approaches have been successfully developed using linear programming (LP) relaxation of the MAP problem. We present an alternative approac...

Full description

Saved in:
Bibliographic Details
Main Authors: KUMAR, Akshat, ZILBERSTEIN, Shlomo
Format: text
Language:English
Published: Institutional Knowledge at Singapore Management University 2010
Subjects:
Artificial Intelligence and Robotics
Operations Research, Systems Engineering and Industrial Engineering
Online Access:https://ink.library.smu.edu.sg/sis_research/2208
https://ink.library.smu.edu.sg/context/sis_research/article/3208/viewcontent/MAP_Estimation_for_Graphical_Models_by_Likelihood_Maximization.pdf
Tags: Add Tag
No Tags, Be the first to tag this record!
Institution: Singapore Management University
Language: English

Internet

https://ink.library.smu.edu.sg/sis_research/2208
https://ink.library.smu.edu.sg/context/sis_research/article/3208/viewcontent/MAP_Estimation_for_Graphical_Models_by_Likelihood_Maximization.pdf

Similar Items