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    ESANN
    2003
    152views Neural Networks» more  ESANN 2003»
    Improving iterative repair strategies for scheduling with the SVM
    15 years 8 months ago
    Improving iterative repair strategies for scheduling with the SVM
    Download  www2.in.tu-clausthal.de
    The resource constraint project scheduling problem (RCPSP) is an NP-hard benchmark problem in scheduling which takes into account the limitation of resources’ availabilities in ...
    Kai Gersmann, Barbara Hammer
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    NAACL
    2004
    127views Computational Linguistics» more  NAACL 2004»
    Robust Reading: Identification and Tracing of Ambiguous Names
    15 years 8 months ago
    Robust Reading: Identification and Tracing of Ambiguous Names
    Download  acl.ldc.upenn.edu
    A given entity, representing a person, a location or an organization, may be mentioned in text in multiple, ambiguous ways. Understanding natural language requires identifying whe...
    Xin Li, Paul Morie, Dan Roth
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    FLAIRS
    2003
    141views Artificial Intelligence» more  FLAIRS 2003»
    Learning from Reinforcement and Advice Using Composite Reward Functions
    15 years 8 months ago
    Learning from Reinforcement and Advice Using Composite Reward Functions
    Download  ranger.uta.edu
    1 Reinforcement learning has become a widely used methodology for creating intelligent agents in a wide range of applications. However, its performance deteriorates in tasks with s...
    Vinay N. Papudesi, Manfred Huber
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    NIPS
    2004
    109views Information Technology» more  NIPS 2004»
    A Large Deviation Bound for the Area Under the ROC Curve
    15 years 8 months ago
    A Large Deviation Bound for the Area Under the ROC Curve
    Download  books.nips.cc
    The area under the ROC curve (AUC) has been advocated as an evaluation criterion for the bipartite ranking problem. We study large deviation properties of the AUC; in particular, ...
    Shivani Agarwal, Thore Graepel, Ralf Herbrich, Dan...
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    NAACL
    2001
    130views Computational Linguistics» more  NAACL 2001»
    Learning Optimal Dialogue Management Rules by Using Reinforcement Learning and Inductive Logic Programming
    15 years 8 months ago
    Learning Optimal Dialogue Management Rules by Using Reinforcement Learning and Inductive Logic Programming
    Download  www.aclweb.org
    Developing dialogue systems is a complex process. In particular, designing efficient dialogue management strategies is often difficult as there are no precise guidelines to develo...
    Renaud Lecoeuche
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