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    ICMLA
    2007
    149views Machine Learning» more  ICMLA 2007»
    Uncertainty optimization for robust dynamic optical flow estimation
    13 years 6 months ago
    Uncertainty optimization for robust dynamic optical flow estimation
    Download  eprints.pascal-network.org
    We develop an optical flow estimation framework that focuses on motion estimation over time formulated in a Dynamic Bayesian Network. It realizes a spatiotemporal integration of ...
    Volker Willert, Marc Toussaint, Julian Eggert, Edg...
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    ICMLA
    2007
    70views Machine Learning» more  ICMLA 2007»
    Learning a knowledge base of ontological concepts for high-level scene interpretation
    13 years 6 months ago
    Learning a knowledge base of ontological concepts for high-level scene interpretation
    Download  kogs-www.informatik.uni-hamburg.de
    Johannes Hartz, Bernd Neumann
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    ICMLA
    2007
    78views Machine Learning» more  ICMLA 2007»
    Machine learned regression for abductive DNA sequencing
    13 years 6 months ago
    Machine learned regression for abductive DNA sequencing
    Download  pubs.doc.ic.ac.uk
    We construct machine learned regressors to predict the behaviour of DNA sequencing data from the fluorescent labelled Sanger method. These predictions are used to assess hypothes...
    David Thornley, Maxim Zverev, Stavros Petridis
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    ICMLA
    2007
    116views Machine Learning» more  ICMLA 2007»
    Maximum Likelihood Quantization of Genomic Features Using Dynamic Programming
    13 years 6 months ago
    Maximum Likelihood Quantization of Genomic Features Using Dynamic Programming
    Download  www.cs.nmsu.edu
    Dynamic programming is introduced to quantize a continuous random variable into a discrete random variable. Quantization is often useful before statistical analysis or reconstruct...
    Mingzhou (Joe) Song, Robert M. Haralick, Sté...
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    ICMLA
    2007
    113views Machine Learning» more  ICMLA 2007»
    Bias-variance tradeoff in hybrid generative-discriminative models
    13 years 6 months ago
    Bias-variance tradeoff in hybrid generative-discriminative models
    Download  eprints.pascal-network.org
    Given any generative classifier based on an inexact density model, we can define a discriminative counterpart that reduces its asymptotic error rate, while increasing the estima...
    Guillaume Bouchard
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