[PDF.30ua] Convex Optimization: Algorithms and Complexity (Foundations and Trends(r) in Machine Learning)

Convex Optimization: Algorithms and Complexity (Foundations and Trends(r) in Machine Learning)

[PDF.ba43] Convex Optimization: Algorithms and Complexity (Foundations and Trends(r) in Machine Learning)

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 | #2329658 in Books |  2015-10-28 | Original language:English | PDF # 1 |  9.21 x.30 x6.14l,.46 | File type: PDF | 142 pages

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This monograph presents the main complexity theorems in convex optimization and their corresponding algorithms. It begins with the fundamental theory of black-box optimization and proceeds to guide the reader through recent advances in structural optimization and stochastic optimization. The presentation of black-box optimization, strongly influenced by the seminal book by Nesterov, includes the analysis of cutting plane methods, as well as (accelerated) gradient descent...

You easily download any file type for your gadget.Convex Optimization: Algorithms and Complexity (Foundations and Trends(r) in Machine Learning)   |  Sébastien Bubeck. I have read it a couple of times and even shared with my family members. Really good. Couldnt put it down.

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