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    NIPS
    1990
    61views Information Technology» more  NIPS 1990»
    Training Knowledge-Based Neural Networks to Recognize Genes
    13 years 6 months ago
    Training Knowledge-Based Neural Networks to Recognize Genes
    Download  ftp.cs.wisc.edu
    Michiel O. Noordewier, Geoffrey G. Towell, Jude W....
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    NIPS
    1990
    102views Information Technology» more  NIPS 1990»
    Planning with an Adaptive World Model
    13 years 6 months ago
    Planning with an Adaptive World Model
    Download  www.ri.cmu.edu
    We present a new connectionist planning method TML90 . By interaction with an unknown environment, a world model is progressively constructed using gradient descent. For deriving ...
    Sebastian Thrun, Knut Möller, Alexander Linde...
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    NIPS
    1990
    121views Information Technology» more  NIPS 1990»
    A Delay-Line Based Motion Detection Chip
    13 years 6 months ago
    A Delay-Line Based Motion Detection Chip
    Download  www.cs.berkeley.edu
    Inspired by a visual motion detection model for the rabbit retina and by a computational architecture used for early audition in the barn owl, we have designed a chip that employs...
    Timothy K. Horiuchi, John Lazzaro, Andrew Moore, C...
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    NIPS
    1990
    115views Information Technology» more  NIPS 1990»
    Back Propagation is Sensitive to Initial Conditions
    13 years 6 months ago
    Back Propagation is Sensitive to Initial Conditions
    Download  www.demo.cs.brandeis.edu
    This paper explores the effect of initial weight selection on feed-forward networks learning simple functions with the back-propagation technique. We first demonstrate, through th...
    John F. Kolen, Jordan B. Pollack
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    NIPS
    1990
    137views Information Technology» more  NIPS 1990»
    Convergence of a Neural Network Classifier
    13 years 6 months ago
    Convergence of a Neural Network Classifier
    Download  www.isr.umd.edu
    In this paper, we show that the LVQ learning algorithm converges to locally asymptotic stable equilibria of an ordinary differential equation. We show that the learning algorithm ...
    John S. Baras, Anthony LaVigna
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