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    TREC
    2004
    103views Information Technology» more  TREC 2004»
    Feature Generation, Feature Selection, Classifiers, and Conceptual Drift for Biomedical Document Triage
    13 years 9 months ago
    Feature Generation, Feature Selection, Classifiers, and Conceptual Drift for Biomedical Document Triage
    Download  trec.nist.gov
    We approached the problem of classifying papers for the TREC 2004 Genomics Track triage task as a four step process: feature generation, feature selection, classifier training, an...
    Aaron M. Cohen, Ravi Teja Bhupatiraju, William R. ...
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    ECAI
    2006
    Springer
    196views Artificial Intelligence» more  ECAI 2006»
    A Learning Classifier Approach to Tomography
    13 years 11 months ago
    A Learning Classifier Approach to Tomography
    Download  webh01.ua.ac.be
    Tomography is an important technique for noninvasive imaging: images of the interior of an object are computed from several scanned projections of the object, covering a range of a...
    Kees Joost Batenburg
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    NAACL
    2003
    149views Computational Linguistics» more  NAACL 2003»
    Semantic Language Models for Topic Detection and Tracking
    13 years 9 months ago
    Semantic Language Models for Topic Detection and Tracking
    Download  www.cs.cmu.edu
    In this work, we present a new semantic language modeling approach to model news stories in the Topic Detection and Tracking (TDT) task. In the new approach, we build a unigram la...
    Ramesh Nallapati
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    EMNLP
    2006
    130views Natural Language Processing» more  EMNLP 2006»
    Loss Minimization in Parse Reranking
    13 years 9 months ago
    Loss Minimization in Parse Reranking
    Download  homepages.inf.ed.ac.uk
    We propose a general method for reranker construction which targets choosing the candidate with the least expected loss, rather than the most probable candidate. Different approac...
    Ivan Titov, James Henderson
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    PRIS
    2004
    104views Pattern Recognition» more  PRIS 2004»
    Neural Network Learning: Testing Bounds on Sample Complexity
    13 years 9 months ago
    Neural Network Learning: Testing Bounds on Sample Complexity
    Download  www.di.ubi.pt
    Several authors have theoretically determined distribution-free bounds on sample complexity. Formulas based on several learning paradigms have been presented. However, little is kn...
    Joaquim Marques de Sá, Fernando Sereno, Lu&...
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