Sciweavers

    61
    Voted
    NIPS
    2000
    115views Information Technology» more  NIPS 2000»
    A PAC-Bayesian Margin Bound for Linear Classifiers: Why SVMs work
    14 years 10 months ago
    A PAC-Bayesian Margin Bound for Linear Classifiers: Why SVMs work
    Download  www.lr.pi.titech.ac.jp
    We investigate how the normalization of vectors influences the result of SVMs. 1 Normalization For the theoretical background, please refer to [1]. 2 Experiments We empirically co...
    Ralf Herbrich, Thore Graepel
    claim paper
    Read More »
    Explore & Download
    Proceedings Preprints Top 5 Ranked Papers Publications Books Software Tutorials Presentations Lectures Notes Datasets
    Productivity Tools
    International On-screen Keyboard Graphical Social Symbols OCR Text Recognition CSS3 Style Generator Web Page to PDF Web Page to Image PDF Split PDF Merge Latex Equation Editor Sci2ools
    Document Tools
    PDF to Text PDF to Postscript PDF to Thumbnails Excel to PDF Word to PDF Postscript to PDF PowerPoint to PDF Latex to Word Repair Corrupted PDF
    Image Tools
    JPG to PS JPG to PDF Extract Images from PDF Image Converter
    Sciweavers
    About Community Cookies Privacy Policy Terms of Use

    Copyright © Sciweavers LLC, 2009-2025, USA.