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    Fast Exact Multiplication by the Hessian

    Pearlmutter, Barak A. (1994) Fast Exact Multiplication by the Hessian. Neural Computation, 6 (1). pp. 147-160. ISSN 0899-7667

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    Just storing the Hessian H (the matrix of second derivatives a2E/aw, aw, of the error E with respect to each pair of weights) of a large neural network is difficult. Since a common use of a large matrix like H is to compute its product with various vectors, we derive a technique that directly calculates Hv, where v is an arbitrary vector. To calculate Hv, we first define a differential operator Rycf (w)}=(a/&) f (w+ W) J~=~, note that%{Vw}= Hv and%{w}= v, and then apply R {.} to the equations used to compute 0,.

    Item Type: Article
    Keywords: Fast Exact Multiplication; Hessian;
    Academic Unit: Faculty of Science and Engineering > Computer Science
    Faculty of Science and Engineering > Research Institutes > Hamilton Institute
    Item ID: 5501
    Depositing User: Barak Pearlmutter
    Date Deposited: 15 Oct 2014 10:21
    Journal or Publication Title: Neural Computation
    Publisher: MIT Press
    Refereed: Yes
    Use Licence: This item is available under a Creative Commons Attribution Non Commercial Share Alike Licence (CC BY-NC-SA). Details of this licence are available here

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