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    FAW
    2008
    Springer
    225views Algorithms» more  FAW 2008»
    Versioning Tree Structures by Path-Merging
    15 years 9 months ago
    Versioning Tree Structures by Path-Merging
    Download  dcg.ethz.ch
    We propose path-merging as a refinement of techniques used to make linked data structures partially persistent. Path-merging supports bursts of operations between any two adjacent ...
    Khaireel A. Mohamed, Tobias Langner, Thomas Ottman...
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    172
    Voted
    NIPS
    2008
    143views Information Technology» more  NIPS 2008»
    Integrating Locally Learned Causal Structures with Overlapping Variables
    15 years 9 months ago
    Integrating Locally Learned Causal Structures with Overlapping Variables
    Download  www.andrew.cmu.edu
    In many domains, data are distributed among datasets that share only some variables; other recorded variables may occur in only one dataset. While there are asymptotically correct...
    Robert E. Tillman, David Danks, Clark Glymour
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    EMNLP
    2006
    190views Natural Language Processing» more  EMNLP 2006»
    Competitive generative models with structure learning for NLP classification tasks
    15 years 9 months ago
    Competitive generative models with structure learning for NLP classification tasks
    Download  nlp.stanford.edu
    In this paper we show that generative models are competitive with and sometimes superior to discriminative models, when both kinds of models are allowed to learn structures that a...
    Kristina Toutanova
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    168
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    COLING
    2000
    92views Computational Linguistics» more  COLING 2000»
    Japanese Case Structure Analysis
    15 years 9 months ago
    Japanese Case Structure Analysis
    Download  kc.nict.go.jp
    In Japanese, case structure analysis is very important to handle several troublesome characteristics of Japanese such as scrambling, omission of case components, and disappearance...
    Daisuke Kawahara, Nobuhiro Kaji, Sadao Kurohashi
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    COLING
    1996
    92views Computational Linguistics» more  COLING 1996»
    FeasPar - A Feature Structure Parser Learning to Parse Spoken Language
    15 years 8 months ago
    FeasPar - A Feature Structure Parser Learning to Parse Spoken Language
    Download  acl.ldc.upenn.edu
    We describe and experimentally evaluate a system, FeasPar, that learns parsing spontaneous speech. To train and run FeasPar (Feature Structure Parser), only limited handmodeled kn...
    Finn Dag Buø, Alex Waibel
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