| 000 -LEADER |
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| fixed length control field |
01997 a2200241 4500 |
| 005 - DATE AND TIME OF LATEST TRANSACTION |
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| control field |
20190530122026.0 |
| 008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION |
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| fixed length control field |
190530b xxu||||| |||| 00| 0 eng d |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER |
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| ISBN |
9783319915777 |
| 040 ## - CATALOGING SOURCE |
|---|
| Transcribing agency |
IIT Kanpur |
| 041 ## - LANGUAGE CODE |
|---|
| Language code of text/sound track or separate title |
eng |
| 082 ## - DEWEY DECIMAL CLASSIFICATION NUMBER |
|---|
| Classification number |
519.3 |
| Item number |
N376l2 |
| 100 ## - MAIN ENTRY--AUTHOR NAME |
|---|
| Personal name |
Nesterov, Yurii |
| 245 ## - TITLE STATEMENT |
|---|
| Title |
Lectures on convex optimization |
| Statement of responsibility, etc |
Yurii Nesterov |
| 250 ## - EDITION STATEMENT |
|---|
| Edition statement |
2nd ed |
| 260 ## - PUBLICATION, DISTRIBUTION, ETC. (IMPRINT) |
|---|
| Name of publisher |
Springer |
| Year of publication |
2018 |
| Place of publication |
Switzerland |
| 300 ## - PHYSICAL DESCRIPTION |
|---|
| Number of Pages |
xxiii, 589p |
| 440 ## - SERIES STATEMENT/ADDED ENTRY--TITLE |
|---|
| Title |
Springer optimization and its applications |
| 490 ## - SERIES STATEMENT |
|---|
| Series statement |
/ edited by Ding-Zhu Du; v.137 |
| 520 ## - SUMMARY, ETC. |
|---|
| Summary, etc |
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. |
| 650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM |
|---|
| Topical Term |
Computers -- Programming -- Algorithms |
| 650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM |
|---|
| Topical Term |
Algorithms & data structures |
| 942 ## - ADDED ENTRY ELEMENTS (KOHA) |
|---|
| Koha item type |
Books |
