[PDF.35kk] Convex Optimization: Algorithms and Complexity (Foundations and Trends(r) in Machine Learning)
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Convex Optimization: Algorithms and Complexity (Foundations and Trends(r) in Machine Learning)
Sébastien Bubeck
[PDF.kw67] Convex Optimization: Algorithms and Complexity (Foundations and Trends(r) in Machine Learning)
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| #2579705 in Books | 2015-10-28 | Original language:English | PDF # 1 | 9.21 x.30 x6.14l,.46 | File type: PDF | 142 pages|
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...
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