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    ACL
    2008
    168views Computational Linguistics» more  ACL 2008»
    Unsupervised Learning of Acoustic Sub-word Units
    13 years 9 months ago
    Unsupervised Learning of Acoustic Sub-word Units
    Download  aclweb.org
    Accurate unsupervised learning of phonemes of a language directly from speech is demonstrated via an algorithm for joint unsupervised learning of the topology and parameters of a ...
    Balakrishnan Varadarajan, Sanjeev Khudanpur, Emman...
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    BCSHCI
    2007
    77views Human Computer Interaction» more  BCSHCI 2007»
    Exploring potential usability gaps when switching mobile phones: an empirical study
    13 years 9 months ago
    Exploring potential usability gaps when switching mobile phones: an empirical study
    Download  www.bcs.org
    The present study explores potential usability gaps when users switch from a familiar to an unfamiliar mobile phone interface. A within-subject experiment was performed in which n...
    Aiko Fallas Yamashita, Wolmet Barendregt, Morten F...
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    CIMAGING
    2008
    165views Hardware» more  CIMAGING 2008»
    Multimodal unbiased image matching via mutual information
    13 years 9 months ago
    Multimodal unbiased image matching via mutual information
    Download  www.math.ucla.edu
    In the past decade, information theory has been studied extensively in computational imaging. In particular, image matching by maximizing mutual information has been shown to yiel...
    Igor Yanovsky, Paul M. Thompson, Stanley Osher, Al...
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    ESANN
    2008
    278views Neural Networks» more  ESANN 2008»
    Learning to play Tetris applying reinforcement learning methods
    13 years 9 months ago
    Learning to play Tetris applying reinforcement learning methods
    Download  www.dice.ucl.ac.be
    In this paper the application of reinforcement learning to Tetris is investigated, particulary the idea of temporal difference learning is applied to estimate the state value funct...
    Alexander Groß, Jan Friedland, Friedhelm Sch...
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    NIPS
    2008
    285views Information Technology» more  NIPS 2008»
    Natural Image Denoising with Convolutional Networks
    13 years 9 months ago
    Natural Image Denoising with Convolutional Networks
    Download  hebb.mit.edu
    We present an approach to low-level vision that combines two main ideas: the use of convolutional networks as an image processing architecture and an unsupervised learning procedu...
    Viren Jain, H. Sebastian Seung
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