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Limited-memory BFGS / BFGS method / Quasi-Newton method / Gradient descent / Orthant-wise limited-memory quasi-Newton / Wolfe conditions / Convex optimization / Hessian matrix / Subderivative / Numerical analysis / Mathematical analysis / Mathematical optimization


Journal of Machine Learning Research–57 Submitted 11/08; Revised 11/09; Published -/10 A Quasi-Newton Approach to Nonsmooth Convex Optimization Problems in Machine Learning
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Document Date: 2010-03-07 22:04:30

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File Size: 2,61 MB

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The University of Adelaide Adelaide SA / Local Quadratic Model / Australia S.V. / DV Bern AG / /

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Product Issues / Product Recall / /

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LBFGS stalls / Computer Science The University of Adelaide Adelaide SA / /

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real-world applications / line search methods / line search conditions / optimization algorithms / inexact line search / jmlr@schraudolph.org adaptive tools / subBFGS algorithm / line search / line search algorithm / search direction / /

Organization

University of Adelaide / Purdue University / /

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Bt / Lemar / Nicol N. Schraudolph / Jin Yu / /

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Editor / /

Product

Generalizing the Local Quadratic / /

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Indiana / /

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Journal of Machine Learning Research / /

Technology

resulting subBFGS algorithm / line search algorithm / optimization algorithms / BFGS algorithm / caching / example Algorithm / Machine Learning / I. All algorithms / /

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