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    ICALT
    2008
    IEEE
    135views Machine Learning» more  ICALT 2008»
    Interaction Analysis as a Multi-Support Approach of Social Computing for Learning, in the "Collaborative Era": Lessons Learned b
    14 years 3 months ago
    Interaction Analysis as a Multi-Support Approach of Social Computing for Learning, in the "Collaborative Era": Lessons Learned b
    Download  ltee.org
    Apparently computer technology is shifting its focus, with individual users not being the main target any more. The evolution of Web 2.0 technologies is promoting the development ...
    Tharrenos Bratitsis, Angelique Dimitracopoulou
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    IADIS
    2004
    104views Internet Technology» more  IADIS 2004»
    Addressing the Effective Use of Learning Objects Through Teacher Education
    13 years 10 months ago
    Addressing the Effective Use of Learning Objects Through Teacher Education
    Download  www.iadis.net
    This paper describes the development and evaluation of a curriculum designed to help teachers learn about and integrate digital library functionalities and learning objects into t...
    Mimi Recker
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    ICML
    2005
    IEEE
    100views Machine Learning» more  ICML 2005»
    Reinforcement learning with Gaussian processes
    14 years 9 months ago
    Reinforcement learning with Gaussian processes
    Download  www.machinelearning.org
    Gaussian Process Temporal Difference (GPTD) learning offers a Bayesian solution to the policy evaluation problem of reinforcement learning. In this paper we extend the GPTD framew...
    Yaakov Engel, Shie Mannor, Ron Meir
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    SIGIR
    2008
    ACM
    192views Information Technology» more  SIGIR 2008»
    Learning to rank with partially-labeled data
    13 years 8 months ago
    Learning to rank with partially-labeled data
    Download  ssli.ee.washington.edu
    Ranking algorithms, whose goal is to appropriately order a set of objects/documents, are an important component of information retrieval systems. Previous work on ranking algorith...
    Kevin Duh, Katrin Kirchhoff
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    ICDM
    2005
    IEEE
    190views Data Mining» more  ICDM 2005»
    Adaptive Clustering: Obtaining Better Clusters Using Feedback and Past Experience
    14 years 2 months ago
    Adaptive Clustering: Obtaining Better Clusters Using Feedback and Past Experience
    Download  www2.cs.uh.edu
    Adaptive clustering uses external feedback to improve cluster quality; past experience serves to speed up execution time. An adaptive clustering environment is proposed that uses ...
    Abraham Bagherjeiran, Christoph F. Eick, Chun-Shen...
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