Relatively Smooth Convex Optimization by First-Order Methods, and Applications

The usual approach to developing and analyzing first-order methods for smooth convex optimization assumes that the gradient of the objective function is uniformly smooth with some Lipschitz constant L. However, in many settings the differentiable convex function f(?) is not uniformly smooth-for exam...

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Bibliographic Details
Main Authors: Nesterov, Yurii (Author), Lu, Haihao (Contributor), Freund, Robert Michael (Contributor)
Other Authors: Massachusetts Institute of Technology. Department of Mathematics (Contributor), Sloan School of Management (Contributor)
Format: Article
Language:English
Published: Society for Industrial & Applied Mathematics (SIAM), 2019-03-11T18:29:55Z.
Subjects:
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