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    NIPS
    1994
    472views Information Technology» more  NIPS 1994»
    Convergence Properties of the K-Means Algorithms
    13 years 6 months ago
    Convergence Properties of the K-Means Algorithms
    Download  www.iro.umontreal.ca
    This paper studies the convergence properties of the well known K-Means clustering algorithm. The K-Means algorithm can be described either as a gradient descent algorithmor by sl...
    Léon Bottou, Yoshua Bengio
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    NIPS
    1994
    264views Information Technology» more  NIPS 1994»
    An Input Output HMM Architecture
    13 years 6 months ago
    An Input Output HMM Architecture
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    We introduce a recurrent architecture having a modular structure and we formulate a training procedure based on the EM algorithm. The resulting model has similarities to hidden Ma...
    Yoshua Bengio, Paolo Frasconi
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    NIPS
    1994
    140views Information Technology» more  NIPS 1994»
    A Non-linear Information Maximisation Algorithm that Performs Blind Separation
    13 years 6 months ago
    A Non-linear Information Maximisation Algorithm that Performs Blind Separation
    Download  eref.uqu.edu.sa
    A new learning algorithmis derived which performs online stochastic gradient ascent in the mutual informationbetween outputs and inputs of a network. In the absence of a priori kn...
    Anthony J. Bell, Terrence J. Sejnowski
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    NIPS
    1994
    148views Information Technology» more  NIPS 1994»
    Real-Time Control of a Tokamak Plasma Using Neural Networks
    13 years 6 months ago
    Real-Time Control of a Tokamak Plasma Using Neural Networks
    Download  research.microsoft.com
    In this paper we present results from the first use of neural networks for real-time control of the high temperature plasma in a tokamak fusion experiment. The tokamak is currentl...
    Christopher M. Bishop
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    NIPS
    1994
    100views Information Technology» more  NIPS 1994»
    Boosting the Performance of RBF Networks with Dynamic Decay Adjustment
    13 years 6 months ago
    Boosting the Performance of RBF Networks with Dynamic Decay Adjustment
    Download  www.inf.uni-konstanz.de
    Radial Basis Function (RBF) Networks, also known as networks of locally{tuned processing units (see 6]) are well known for their ease of use. Most algorithms used to train these t...
    Michael R. Berthold, Jay Diamond
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    NIPS
    1994
    107views Information Technology» more  NIPS 1994»
    On-line Learning of Dichotomies
    13 years 6 months ago
    On-line Learning of Dichotomies
    Download  hebb.mit.edu
    The performance of on-line algorithms for learning dichotomies is studied. In on-line learning, the number of examples P is equivalent to the learning time, since each example is ...
    N. Barkai, H. Sebastian Seung, Haim Sompolinsky
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    NIPS
    1994
    97views Information Technology» more  NIPS 1994»
    Using a Saliency Map for Active Spatial Selective Attention: Implementation & Initial Results
    13 years 6 months ago
    Using a Saliency Map for Active Spatial Selective Attention: Implementation & Initial Results
    Download  www.ri.cmu.edu
    Shumeet Baluja, Dean Pomerleau
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    NIPS
    1993
    86views Information Technology» more  NIPS 1993»
    Developing Population Codes by Minimizing Description Length
    13 years 6 months ago
    Developing Population Codes by Minimizing Description Length
    Download  www.cs.toronto.edu
    Richard S. Zemel, Geoffrey E. Hinton
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    NIPS
    1993
    89views Information Technology» more  NIPS 1993»
    Postal Address Block Location Using a Convolutional Locator Network
    13 years 6 months ago
    Postal Address Block Location Using a Convolutional Locator Network
    Download  research.microsoft.com
    This paper describes the use of a convolutional neural network to perform address block location on machine-printed mail pieces. Locating the address block is a dicult object rec...
    Ralph Wolf, John C. Platt
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    NIPS
    1993
    86views Information Technology» more  NIPS 1993»
    Robust Reinforcement Learning in Motion Planning
    13 years 6 months ago
    Robust Reinforcement Learning in Motion Planning
    Download  www.cs.cmu.edu
    While exploring to nd better solutions, an agent performing online reinforcement learning (RL) can perform worse than is acceptable. In some cases, exploration might have unsafe, ...
    Satinder P. Singh, Andrew G. Barto, Roderic A. Gru...
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