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    » Analysis of Perceptron-Based Active Learning
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    EWSPT
    2003
    Springer
    146views Software Engineering» more  EWSPT 2003»
    Lessons Learned and Recommendations from Two Large Norwegian SPI Programmes
    14 years 22 days ago
    Lessons Learned and Recommendations from Two Large Norwegian SPI Programmes
    Download  www.idi.ntnu.no
    : Software development is an experimental discipline, i.e. somewhat unpredictable. This suggests that software processes improvement should be based on the continuous iteration of ...
    Reidar Conradi, Tore Dybå, Dag I. K. Sj&osla...
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    SIGCSE
    1996
    ACM
    163views Education» more  SIGCSE 1996»
    Database theory in practice: learning from cooperative group projects
    13 years 11 months ago
    Database theory in practice: learning from cooperative group projects
    Download  www.public.asu.edu
    lhis paper describes the use of cooperative group learning concepts in support of an undergraduate database mrtnagement course that emphasizes the theoretical and practical aspect...
    Suzanne W. Dietrich, Susan Darling Urban
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    IJCAI
    1997
    155views Artificial Intelligence» more  IJCAI 1997»
    Machine Learning Techniques to Make Computers Easier to Use
    13 years 8 months ago
    Machine Learning Techniques to Make Computers Easier to Use
    Download  www.ar.sanken.osaka-u.ac.jp
    Identifying user-dependent information that can be automatically collected helps build a user model by which 1) to predict what the user wants to do next and 2) to do relevant pre...
    Hiroshi Motoda, Kenichi Yoshida
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    IJON
    2007
    117views more  IJON 2007»
    Learning sensory representations with intrinsic plasticity
    13 years 7 months ago
    Learning sensory representations with intrinsic plasticity
    Download  fias.uni-frankfurt.de
    Intrinsic plasticity (IP) refers to a neuron’s ability to regulate its firing activity by adapting its intrinsic excitability. Previously, we showed that model neurons combinin...
    Nicholas Butko, Jochen Triesch
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    SIGECOM
    2009
    ACM
    114views ECommerce» more  SIGECOM 2009»
    Policy teaching through reward function learning
    14 years 2 months ago
    Policy teaching through reward function learning
    Download  www.eecs.harvard.edu
    Policy teaching considers a Markov Decision Process setting in which an interested party aims to influence an agent’s decisions by providing limited incentives. In this paper, ...
    Haoqi Zhang, David C. Parkes, Yiling Chen
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