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    EMNLP
    2008
    199views Natural Language Processing» more  EMNLP 2008»
    Acquiring Domain-Specific Dialog Information from Task-Oriented Human-Human Interaction through an Unsupervised Learning
    15 years 8 months ago
    Acquiring Domain-Specific Dialog Information from Task-Oriented Human-Human Interaction through an Unsupervised Learning
    Download  www.aclweb.org
    We describe an approach for acquiring the domain-specific dialog knowledge required to configure a task-oriented dialog system that uses human-human interaction data. The key aspe...
    Ananlada Chotimongkol, Alexander I. Rudnicky
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    NIPS
    2007
    190views Information Technology» more  NIPS 2007»
    Sparse Feature Learning for Deep Belief Networks
    15 years 8 months ago
    Sparse Feature Learning for Deep Belief Networks
    Download  www.cs.nyu.edu
    Unsupervised learning algorithms aim to discover the structure hidden in the data, and to learn representations that are more suitable as input to a supervised machine than the ra...
    Marc'Aurelio Ranzato, Y-Lan Boureau, Yann LeCun
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    FLAIRS
    2004
    106views Artificial Intelligence» more  FLAIRS 2004»
    On the Pedagogically Guided Paper Recommendation for an Evolving Web-Based Learning System
    15 years 8 months ago
    On the Pedagogically Guided Paper Recommendation for an Evolving Web-Based Learning System
    Download  www.aaai.org
    In this paper we discuss the mechanism of a recommender system recommending papers for an evolving web-based learning system. Our system is unique in three aspects. The first is t...
    Tiffany Ya Tang, Gordon I. McCalla
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    UAI
    2003
    102views Artificial Intelligence» more  UAI 2003»
    Learning Module Networks
    15 years 8 months ago
    Learning Module Networks
    Download  jmlr.csail.mit.edu
    Methods for learning Bayesian networks can discover dependency structure between observed variables. Although these methods are useful in many applications, they run into computat...
    Eran Segal, Dana Pe'er, Aviv Regev, Daphne Koller,...
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    ICML
    2010
    IEEE
    181views Machine Learning» more  ICML 2010»
    Learning Markov Logic Networks Using Structural Motifs
    15 years 7 months ago
    Learning Markov Logic Networks Using Structural Motifs
    Download  www.cs.washington.edu
    Markov logic networks (MLNs) use firstorder formulas to define features of Markov networks. Current MLN structure learners can only learn short clauses (4-5 literals) due to extre...
    Stanley Kok, Pedro Domingos
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