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    NIPS
    1997
    96views Information Technology» more  NIPS 1997»
    Learning Generative Models with the Up-Propagation Algorithm
    13 years 6 months ago
    Learning Generative Models with the Up-Propagation Algorithm
    Download  hebb.mit.edu
    Up-propagation is an algorithm for inverting and learning neural network generative models. Sensory input is processed by inverting a model that generates patterns from hidden var...
    Jong-Hoon Oh, H. Sebastian Seung
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    NIPS
    1997
    91views Information Technology» more  NIPS 1997»
    A Hippocampal Model of Recognition Memory
    13 years 6 months ago
    A Hippocampal Model of Recognition Memory
    Download  compmem.princeton.edu
    A rich body of data exists showing that recollection of specific information makes an important contribution to recognition memory, which is distinct from the contribution of fam...
    Randall C. O'Reilly, Kenneth A. Norman, James L. M...
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    NIPS
    1997
    92views Information Technology» more  NIPS 1997»
    Learning to Schedule Straight-Line Code
    13 years 6 months ago
    Learning to Schedule Straight-Line Code
    Download  homepages.inf.ed.ac.uk
    Program execution speed on modern computers is sensitive, by a factor of two or more, to the order in which instructions are presented to the processor. To realize potential execu...
    J. Eliot B. Moss, Paul E. Utgoff, John Cavazos, Do...
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    NIPS
    1997
    189views Information Technology» more  NIPS 1997»
    A Framework for Multiple-Instance Learning
    13 years 6 months ago
    A Framework for Multiple-Instance Learning
    Download  people.csail.mit.edu
    Multiple-instance learning is a variation on supervised learning, where the task is to learn a concept given positive and negative bags of instances. Each bag may contain many ins...
    Oded Maron, Tomás Lozano-Pérez
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    NIPS
    1997
    87views Information Technology» more  NIPS 1997»
    Visual Navigation in a Robot Using Zig-Zag Behavior
    13 years 6 months ago
    Visual Navigation in a Robot Using Zig-Zag Behavior
    Download  www.iguana-robotics.com
    M. Anthony Lewis
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    NIPS
    1997
    57views Information Technology» more  NIPS 1997»
    Learning Nonlinear Overcomplete Representations for Efficient Coding
    13 years 6 months ago
    Learning Nonlinear Overcomplete Representations for Efficient Coding
    Download  papers.cnl.salk.edu
    Michael S. Lewicki, Terrence J. Sejnowski
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    NIPS
    1997
    77views Information Technology» more  NIPS 1997»
    Multi-modular Associative Memory
    13 years 6 months ago
    Multi-modular Associative Memory
    Download  www.cs.tau.ac.il
    Recent imaging studies suggest that object knowledge is stored in the brain as a distributed network of many cortical areas. Motivated by these observations, we study a multi-modu...
    Nir Levy, David Horn, Eytan Ruppin
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    NIPS
    1997
    91views Information Technology» more  NIPS 1997»
    A Neural Network Based Head Tracking System
    13 years 6 months ago
    A Neural Network Based Head Tracking System
    Download  hebb.mit.edu
    We have constructed an inexpensive, video-based, motorized tracking system that learns to track a head. It uses real time graphical user inputs or an auxiliary infrared detector a...
    Daniel D. Lee, H. Sebastian Seung
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    NIPS
    1997
    116views Information Technology» more  NIPS 1997»
    Learning Human-like Knowledge by Singular Value Decomposition: A Progress Report
    13 years 6 months ago
    Learning Human-like Knowledge by Singular Value Decomposition: A Progress Report
    Download  lsa.colorado.edu
    Singular value decomposition (SVD) can be viewed as a method for unsupervised training of a network that associates two classes of events reciprocally by linear connections throug...
    Thomas K. Landauer, Darrell Laham, Peter W. Foltz
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    NIPS
    1997
    79views Information Technology» more  NIPS 1997»
    Relative Loss Bounds for Multidimensional Regression Problems
    13 years 6 months ago
    Relative Loss Bounds for Multidimensional Regression Problems
    Download  users.soe.ucsc.edu
    We study on-line generalized linear regression with multidimensional outputs, i.e., neural networks with multiple output nodes but no hidden nodes. We allow at the final layer tra...
    Jyrki Kivinen, Manfred K. Warmuth
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