Learning with Submodular Functions: A Convex Optimization Perspective
نویسندگان
چکیده
منابع مشابه
Learning with Submodular Functions: A Convex Optimization Perspective
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 Lovász extension of submodular functions provides a useful set of regularization functions for supervised and unsupervised learning. In this monograph, we present the theory of submodular functions from a convex analy...
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Set-functions appear in many areas of computer science and applied mathematics, such as machine learning [1, 2, 3, 4], computer vision [5, 6], operations research [7] or electrical networks [8]. Among these set-functions, submodular functions play an important role, similar to convex functions on vector spaces. In this tutorial, the theory of submodular functions is presented, in a self-contain...
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ژورنال
عنوان ژورنال: Foundations and Trends® in Machine Learning
سال: 2013
ISSN: 1935-8237,1935-8245
DOI: 10.1561/2200000039