|Affiliations:||Mathematical Institute of the Serbian Academy of Sciences and Arts||Title:||Gradient computation in linear-chain conditional random fields using the entropy message passing algorithm||Journal:||Pattern Recognition Letters||Volume:||33||Issue:||13||First page:||1776||Last page:||1784||Issue Date:||1-Oct-2012||Rank:||M22||ISSN:||0167-8655||DOI:||10.1016/j.patrec.2012.05.017||Abstract:||
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.
|Keywords:||Conditional random fields | Expectation semiring | Forward-backward algorithm | Gradient computation | Graphical models | Message passing||Publisher:||Elsevier||Project:||Development of methods of computation and information processing: theory and applications
Development of new information and communication technologies, based on advanced mathematical methods, with applications in medicine, telecommunications, power systems, protection of national heritage and education
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