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    » How SVMs can estimate quantiles and the median
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    CSDA
    2007
    127views more  CSDA 2007»
    Computing the least quartile difference estimator in the plane
    13 years 5 months ago
    Computing the least quartile difference estimator in the plane
    Download  www.statistik.uni-dortmund.de
    A common problem in linear regression is that largely aberrant values can strongly influence the results. The least quartile difference (LQD) regression estimator is highly robus...
    Thorsten Bernholt, Robin Nunkesser, Karen Schettli...
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    EOR
    2008
    90views more  EOR 2008»
    Quality of service statistics over heterogeneous networks: Analysis and applications
    13 years 5 months ago
    Quality of service statistics over heterogeneous networks: Analysis and applications
    Download  wpage.unina.it
    Heterogeneous wireless/wired networks and ubiquitous environments are gaining ever more attention by research community. To properly control and manage such puzzles a deep knowled...
    Alessio Botta, Antonio Pescapè, Giorgio Ven...
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    BMCBI
    2008
    124views more  BMCBI 2008»
    A probe-treatment-reference (PTR) model for the analysis of oligonucleotide expression microarrays
    13 years 5 months ago
    A probe-treatment-reference (PTR) model for the analysis of oligonucleotide expression microarrays
    Download  www.biomedcentral.com
    Background: Microarray pre-processing usually consists of normalization and summarization. Normalization aims to remove non-biological variations across different arrays. The norm...
    Huanying Ge, Chao Cheng, Lei M. Li
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    COMPGEOM
    2004
    ACM
    103views Discrete Geometry» more  COMPGEOM 2004»
    Deterministic sampling and range counting in geometric data streams
    13 years 11 months ago
    Deterministic sampling and range counting in geometric data streams
    Download  www.ics.uci.edu
    We present memory-efficient deterministic algorithms for constructing -nets and -approximations of streams of geometric data. Unlike probabilistic approaches, these deterministic...
    Amitabha Bagchi, Amitabh Chaudhary, David Eppstein...
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    ML
    2002
    ACM
    220views Machine Learning» more  ML 2002»
    Bayesian Methods for Support Vector Machines: Evidence and Predictive Class Probabilities
    13 years 5 months ago
    Bayesian Methods for Support Vector Machines: Evidence and Predictive Class Probabilities
    Download  www.mth.kcl.ac.uk
    I describe a framework for interpreting Support Vector Machines (SVMs) as maximum a posteriori (MAP) solutions to inference problems with Gaussian Process priors. This probabilisti...
    Peter Sollich
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