Learning with Submodular Functions: A Convex Optimization Perspective

by Francis Bach

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Submodular functions are relevant to machine learning for at least two reasons: (1) some problems may be expressed directly as the optimization of submodular functions, and (2) the Lov sz extension of submodular functions provides a useful set of regularization functions for supervised and unsupervised learning. In Learning with Submodular Functions: A Convex Optimization Perspective, the theory of submodular functions is presented in a self-contained...

Format:Paperback

Language:English

ISBN:1601987560

ISBN13:9781601987563

Release Date:December 2013

Publisher:Now Publishers

Length:258 Pages

Weight:0.81 lbs.

Dimensions:0.5" x 6.1" x 9.2"

Related Subjects

Computers Computers & Technology

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Learning with Submodular Functions: A Convex Optimization Perspective

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