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    NIPS
    1998
    105views Information Technology» more  NIPS 1998»
    Divisive Normalization, Line Attractor Networks and Ideal Observers
    13 years 5 months ago
    Divisive Normalization, Line Attractor Networks and Ideal Observers
    Download  www.gatsby.ucl.ac.uk
    Gain control by divisive inhibition, a.k.a. divisive normalization, has been proposed to be a general mechanism throughout the visual cortex. We explore in this study the statisti...
    Sophie Deneve, Alexandre Pouget, Peter E. Latham
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    NIPS
    1998
    107views Information Technology» more  NIPS 1998»
    Example-Based Image Synthesis of Articulated Figures
    13 years 5 months ago
    Example-Based Image Synthesis of Articulated Figures
    Download  www.eecs.berkeley.edu
    We present a method for learning complex appearance mappings, such as occur with images of articulated objects. Traditional interpolation networks fail on this case since appearan...
    Trevor Darrell
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    NIPS
    1998
    184views Information Technology» more  NIPS 1998»
    Facial Memory Is Kernel Density Estimation (Almost)
    13 years 5 months ago
    Facial Memory Is Kernel Density Estimation (Almost)
    Download  www.cs.ait.ac.th
    We compare the ability of three exemplar-based memory models, each using three different face stimulus representations, to account for the probability a human subject responded &q...
    Matthew N. Dailey, Garrison W. Cottrell, Thomas A....
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    NIPS
    1998
    138views Information Technology» more  NIPS 1998»
    Dynamically Adapting Kernels in Support Vector Machines
    13 years 5 months ago
    Dynamically Adapting Kernels in Support Vector Machines
    Download  www.support-vector.net
    The kernel-parameter is one of the few tunable parameters in Support Vector machines, controlling the complexity of the resulting hypothesis. Its choice amounts to model selection...
    Nello Cristianini, Colin Campbell, John Shawe-Tayl...
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    NIPS
    1998
    67views Information Technology» more  NIPS 1998»
    A Phase Space Approach to Minimax Entropy Learning and the Minutemax Approximations
    13 years 5 months ago
    A Phase Space Approach to Minimax Entropy Learning and the Minutemax Approximations
    Download  www.stat.ucla.edu
    There has been much recent work on measuring image statistics and on learning probability distributions on images. We observe that the mapping from images to statistics is many-to...
    James M. Coughlan, Alan L. Yuille
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    NIPS
    1998
    117views Information Technology» more  NIPS 1998»
    Fisher Scoring and a Mixture of Modes Approach for Approximate Inference and Learning in Nonlinear State Space Models
    13 years 5 months ago
    Fisher Scoring and a Mixture of Modes Approach for Approximate Inference and Learning in Nonlinear State Space Models
    Download  www.gatsby.ucl.ac.uk
    We present Monte-Carlo generalized EM equations for learning in nonlinear state space models. The dif
    Thomas Briegel, Volker Tresp
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    NIPS
    1998
    102views Information Technology» more  NIPS 1998»
    An Entropic Estimator for Structure Discovery
    13 years 5 months ago
    An Entropic Estimator for Structure Discovery
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    We introduce a novel framework for simultaneous structure and parameter learning in hidden-variable conditional probability models, based on an entropic prior and a solution for i...
    Matthew Brand
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    NIPS
    1998
    164views Information Technology» more  NIPS 1998»
    Approximate Learning of Dynamic Models
    13 years 5 months ago
    Approximate Learning of Dynamic Models
    Download  robotics.stanford.edu
    Inference is a key component in learning probabilistic models from partially observable data. When learning temporal models, each of the many inference phases requires a complete ...
    Xavier Boyen, Daphne Koller
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    NIPS
    1998
    131views Information Technology» more  NIPS 1998»
    Lazy Learning Meets the Recursive Least Squares Algorithm
    13 years 5 months ago
    Lazy Learning Meets the Recursive Least Squares Algorithm
    Download  www.swarm-bots.org
    Lazy learning is a memory-based technique that, once a query is received, extracts a prediction interpolating locally the neighboring examples of the query which are considered re...
    Mauro Birattari, Gianluca Bontempi, Hugues Bersini
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    NIPS
    1998
    89views Information Technology» more  NIPS 1998»
    Evidence for a Forward Dynamics Model in Human Adaptive Motor Control
    13 years 5 months ago
    Evidence for a Forward Dynamics Model in Human Adaptive Motor Control
    Download  www.shadmehrlab.org
    Nikhil Bhushan, Reza Shadmehr
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