Sparse Forward-Backward Using Minimum Divergence Beams for Fast Training Of Conditional Random Fields. Pal, C., Sutton, C. A., & McCallum, A. In 2006 IEEE International Conference on Acoustics Speech and Signal Processing (ICASSP), Toulouse, France, May 14-19, 2006, pages 581–584, 2006. IEEE.
Sparse Forward-Backward Using Minimum Divergence Beams for Fast Training Of Conditional Random Fields [link]Paper  doi  bibtex   
@inproceedings{DBLP:conf/icassp/PalSM06,
 author = {Chris Pal and Charles A. Sutton and Andrew McCallum},
 bibsource = {dblp computer science bibliography, http://dblp.org},
 biburl = {http://dblp.org/rec/bib/conf/icassp/PalSM06},
 booktitle = {2006 {IEEE} International Conference on Acoustics Speech and Signal Processing ({ICASSP}), Toulouse, France, May 14-19, 2006},
 doi = {10.1109/ICASSP.2006.1661342},
 url = {https://doi.org/10.1109/ICASSP.2006.1661342},
 pages = {581--584},
 publisher = {IEEE},
 timestamp = {Fri, 19 May 2017 01:00:00 +0200},
 title = {Sparse Forward-Backward Using Minimum Divergence Beams for Fast Training Of Conditional Random Fields},
 year = {2006},
 sum  = {An alternative method for beam-search based on variational principles. Enables not only faster test-time performance of large-state-space CRFs, but this method makes beam search robust enough to be used at training time, enabling dramatically faster learning of discriminative finite-state methods for speech, IE and other applications.}
}

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