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    ICML
    2002
    IEEE
    156views Machine Learning» more  ICML 2002»
    Active + Semi-supervised Learning = Robust Multi-View Learning
    16 years 7 months ago
    Active + Semi-supervised Learning = Robust Multi-View Learning
    Download  www.isi.edu
    In a multi-view problem, the features of the domain can be partitioned into disjoint subsets (views) that are sufficient to learn the target concept. Semi-supervised, multi-view a...
    Ion Muslea, Steven Minton, Craig A. Knoblock
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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
    16 years 1 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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    ECTEL
    2010
    Springer
    108views Machine Learning» more  ECTEL 2010»
    Deep Learning Design for Sustainable Innovation within Shifting Learning Landscapes
    15 years 8 months ago
    Deep Learning Design for Sustainable Innovation within Shifting Learning Landscapes
    Download  publications.andreas.schmidt.name
    Changes in the underpinning technologies for TEL is occurring at a pace that we have never before experienced, and this is unlikely to slow down. This necessitates a broader and mo...
    Andrew Ravenscroft, Tom Boyle, John Cook, Andreas ...
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    ICML
    2005
    IEEE
    127views Machine Learning» more  ICML 2005»
    Exploration and apprenticeship learning in reinforcement learning
    16 years 7 months ago
    Exploration and apprenticeship learning in reinforcement learning
    Download  ai.stanford.edu
    We consider reinforcement learning in systems with unknown dynamics. Algorithms such as E3 (Kearns and Singh, 2002) learn near-optimal policies by using "exploration policies...
    Pieter Abbeel, Andrew Y. Ng
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    AIIDE
    2006
    180views Artificial Intelligence» more  AIIDE 2006»
    Designing a Reinforcement Learning-based Adaptive AI for Large-Scale Strategy Games
    15 years 8 months ago
    Designing a Reinforcement Learning-based Adaptive AI for Large-Scale Strategy Games
    Download  www.aaai.org
    This paper investigates the challenges posed by the application of reinforcement learning to large-scale strategy games. In this context, we present steps and techniques which syn...
    Charles A. G. Madeira, Vincent Corruble, Geber Ram...
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