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    GRAPHICSINTERFACE
    1998
    106views Computer Graphics» more  GRAPHICSINTERFACE 1998»
    On Approximating Rough Curves with Fractal Functions
    15 years 5 months ago
    On Approximating Rough Curves with Fractal Functions
    Download  graphics.cs.uiuc.edu
    Fractal functions are explored as a representation for rough data in computer graphics. Two new techniques for using fractal interpolation functions to approximate rough functions...
    Wayne O. Cochran, John C. Hart, Patrick J. Flynn
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    ISIWI
    1998
    93views Knowledge Management» more  ISIWI 1998»
    SO-grams: a personal visualisation toolkit for intranet users
    15 years 5 months ago
    SO-grams: a personal visualisation toolkit for intranet users
    Download  www.informationswissenschaft.org
    Background The origins of the social browser concept Level one: 'draw and describe' Level two: 'draw and describe' and 'point and click' Level three:...
    Elisabeth Davenport, Kathy Buckner
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    143
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    MCU
    1998
    170views Hardware» more  MCU 1998»
    About the Universality of the Billiard ball model
    15 years 5 months ago
    About the Universality of the Billiard ball model
    Download  www.univ-orleans.fr
    Block cellular automata (BCA) make local, parallel, synchronous and uniform updates of in nite lattices. In the one-dimensionalcase, there exist BCA with 11 states which are unive...
    Jérôme Olivier Durand-Lose
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    123
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    NIPS
    1998
    95views Information Technology» more  NIPS 1998»
    Maximum Conditional Likelihood via Bound Maximization and the CEM Algorithm
    15 years 5 months ago
    Maximum Conditional Likelihood via Bound Maximization and the CEM Algorithm
    Download  www.cs.columbia.edu
    We present the CEM (Conditional Expectation Maximization) algorithm as an extension of the EM (Expectation Maximization) algorithm to conditional density estimation under missing ...
    Tony Jebara, Alex Pentland
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    130
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    NIPS
    1998
    121views Information Technology» more  NIPS 1998»
    Inference in Multilayer Networks via Large Deviation Bounds
    15 years 5 months ago
    Inference in Multilayer Networks via Large Deviation Bounds
    Download  www.cis.upenn.edu
    We study probabilistic inference in large, layered Bayesian networks represented as directed acyclic graphs. We show that the intractability of exact inference in such networks do...
    Michael J. Kearns, Lawrence K. Saul
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