Gradient computation in linear-chain conditional random fields using the entropy message passing algorithm

作     者：Ilic, Velimir M. Mancev, Dejan I. Todorovic, Branimir T. Stankovic, Miomir S. 

作者机构：Serbian Acad Arts & Sci Math Inst Belgrade 11000 Serbia Univ Nis Fac Sci & Math Nish 18000 Serbia Univ Nis Fac Occupat Safety Nish 18000 Serbia 

出 版 物：《PATTERN RECOGNITION LETTERS》 (模式识别快报)

年 卷 期：2012年第33卷第13期

页      面：1776-1784页

核心收录：

学科分类：08[工学] 0812[工学-计算机科学与技术（可授工学、理学学位）] 

基　　金：Ministry of Education and Science of the Republic of Serbia [174013  11144006] 

主　　题：Conditional random fields Expectation semiring Forward-backward algorithm Gradient computation Graphical models Message passing 

摘      要：The paper proposes a numerically stable recursive algorithm for the exact computation of the linear-chain conditional random field gradient. It operates as a forward algorithm over the log-domain expectation semiring and has the purpose of enhancing memory efficiency when applied to long observation sequences. Unlike the traditional algorithm based on the forward-backward recursions, the memory complexity of our algorithm does not depend on the sequence length. The experiments on real data show that it can be useful for the problems which deal with long sequences. (c) 2012 Elsevier B.V. All rights reserved.