Lectures on convex optimization
By: Nesterov, Yurii.
Series: Springer optimization and its applications. / edited by Ding-Zhu Du; v.137.Publisher: Switzerland Springer 2018Edition: 2nd ed.Description: xxiii, 589p.ISBN: 9783319915777.Subject(s): Computers -- Programming -- Algorithms | Algorithms & data structuresDDC classification: 519.3 | N376l2 Summary: This book provides a comprehensive, modern introduction to convex optimization, a field that is becoming increasingly important in applied mathematics, economics and finance, engineering, and computer science, notably in data science and machine learning. Written by a leading expert in the field, this book includes recent advances in the algorithmic theory of convex optimization, naturally complementing the existing literature. It contains a unified and rigorous presentation of the acceleration techniques for minimization schemes of first- and second-order. It provides readers with a full treatment of the smoothing technique, which has tremendously extended the abilities of gradient-type methods. Several powerful approaches in structural optimization, including optimization in relative scale and polynomial-time interior-point methods, are also discussed in detail. Researchers in theoretical optimization as well as professionals working on optimization problems will find this book very useful. It presents many successful examples of how to develop very fast specialized minimization algorithms. Based on the author’s lectures, it can naturally serve as the basis for introductory and advanced courses in convex optimization for students in engineering, economics, computer science and mathematics.| Item type | Current location | Collection | Call number | Status | Date due | Barcode | Item holds |
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Books
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PK Kelkar Library, IIT Kanpur | General Stacks | 519.3 N376l2 (Browse shelf) | Checked out to Abhinav Joshi (S2021126100) | 26/09/2024 | A184419 |
Browsing PK Kelkar Library, IIT Kanpur Shelves , Collection code: General Stacks Close shelf browser
| 519.3 M992g cop.3 Game theory | 519.3 N145d Differentiable optimization and equation solving | 519.3 N164g Game theory and mechanism design [ILNS 4] | 519.3 N376l2 Lectures on convex optimization | 519.3 N42 New ideas in optimization | 519.3 Ou8n Nonsmooth approach to optimization problems with equilibrium constraints | 519.3 P198p2 Principles of optimal design |
This book provides a comprehensive, modern introduction to convex optimization, a field that is becoming increasingly important in applied mathematics, economics and finance, engineering, and computer science, notably in data science and machine learning. Written by a leading expert in the field, this book includes recent advances in the algorithmic theory of convex optimization, naturally complementing the existing literature. It contains a unified and rigorous presentation of the acceleration techniques for minimization schemes of first- and second-order. It provides readers with a full treatment of the smoothing technique, which has tremendously extended the abilities of gradient-type methods. Several powerful approaches in structural optimization, including optimization in relative scale and polynomial-time interior-point methods, are also discussed in detail. Researchers in theoretical optimization as well as professionals working on optimization problems will find this book very useful. It presents many successful examples of how to develop very fast specialized minimization algorithms. Based on the author’s lectures, it can naturally serve as the basis for introductory and advanced courses in convex optimization for students in engineering, economics, computer science and mathematics.
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