San Francisco / Boulder / New York / Morristown / Cambridge / Washington / Honolulu / /
Company
Neural Information Processing Systems / MIT Press / CRFs / Morgan Kaufmann Publishers Inc. / Human Language Technology / Conditional Random Fields / NEC Labs America Inc / Google / /
Country
United States / / /
Facility
University of Rochester / New York University / Rutgers University / /
IndustryTerm
real natural language processing tasks / iterative semi-supervised training algorithm / semi-supervised algorithms / iterative algorithm / natural language processing tasks / recent tagging systems / data mining / online systems / natural language processing systems / semi-supervised learning systems / natural language processing / end applications / cyclic dependency network / language processing tasks / learning algorithms / semi-supervised algorithm / /
Organization
MIT / Rutgers University / Association of Computational Linguistics / University of Rochester / New York University / New York / US Federal Reserve / North American Chapter / Association for Computational Linguistics / /
Person
Kunihiko Sadamasa / Chris Lewis / Pavel Kuksa / Jason Weston / Erik De Meulder / Semi-Supervised Sequence Labeling / F. De Meulder / /
Position
Captain / forward / /
Product
Viterbi / /
ProgrammingLanguage
BASIC / C / /
ProvinceOrState
Hawaii / New York / Massachusetts / Colorado / /
PublishedMedium
Computational Linguistics / Machine Learning / IEEE Transactions on Information Theory / Journal of Machine Learning Research / /
Technology
dynamic algorithm / This algorithm / tagging algorithm / machine translation / semi-supervised algorithms / Machine Learning / semi-supervised algorithm / natural language processing / Knowledge Management / neural network / data mining / following iterative semi-supervised training algorithm / iterative algorithm / /