Lectures on convex optimization /
Saved in:
| Author / Creator: | Nesterov, I︠U︡. E., author. |
|---|---|
| Edition: | Second edition. |
| Imprint: | Cham, Switzerland : Springer, 2018. |
| Description: | 1 online resource (xxiii, 589 pages) : illustrations |
| Language: | English |
| Series: | Springer optimization and its applications, 1931-6828 ; volume 137 Springer optimization and its applications ; v. 137. |
| Subject: | |
| Format: | E-Resource Book |
| URL for this record: | http://pi.lib.uchicago.edu/1001/cat/bib/11737842 |
MARC
| LEADER | 00000cam a2200000Ii 4500 | ||
|---|---|---|---|
| 001 | 11737842 | ||
| 006 | m o d | ||
| 007 | cr cnu|||unuuu | ||
| 008 | 181204s2018 sz a ob 001 0 eng d | ||
| 005 | 20240702155626.9 | ||
| 015 | |a GBB907501 |2 bnb | ||
| 015 | |a GBB917463 |2 bnb | ||
| 016 | 7 | |a 019198553 |2 Uk | |
| 019 | |a 1203983426 |a 1231615243 |a 1249692913 | ||
| 020 | |a 9783319915784 |q (electronic bk.) | ||
| 020 | |a 3319915789 |q (electronic bk.) | ||
| 020 | |a 3319915770 | ||
| 020 | |a 9783319915777 | ||
| 020 | |z 9783319915777 |q (print) | ||
| 024 | 7 | |a 10.1007/978-3-319-91578-4 |2 doi | |
| 035 | |a (OCoLC)1077287529 |z (OCoLC)1203983426 |z (OCoLC)1231615243 |z (OCoLC)1249692913 | ||
| 035 | 9 | |a (OCLCCM-CC)1077287529 | |
| 037 | |a com.springer.onix.9783319915784 |b Springer Nature | ||
| 040 | |a GW5XE |b eng |e rda |e pn |c GW5XE |d FIE |d STF |d OCLCF |d VT2 |d UKMGB |d OCLCQ |d UKAHL |d EBLCP |d DCT |d SFB |d N$T | ||
| 049 | |a MAIN | ||
| 050 | 4 | |a QA402.5 | |
| 072 | 7 | |a PBU |2 bicssc | |
| 072 | 7 | |a MAT003000 |2 bisacsh | |
| 072 | 7 | |a PBU |2 thema | |
| 100 | 1 | |a Nesterov, I︠U︡. E., |e author. |0 http://id.loc.gov/authorities/names/n86082035 | |
| 245 | 1 | 0 | |a Lectures on convex optimization / |c Yurii Nesterov. |
| 250 | |a Second edition. | ||
| 264 | 1 | |a Cham, Switzerland : |b Springer, |c 2018. | |
| 300 | |a 1 online resource (xxiii, 589 pages) : |b illustrations | ||
| 336 | |a text |b txt |2 rdacontent | ||
| 337 | |a computer |b c |2 rdamedia | ||
| 338 | |a online resource |b cr |2 rdacarrier | ||
| 347 | |a text file |b PDF |2 rda | ||
| 490 | 1 | |a Springer optimization and its applications, |x 1931-6828 ; |v volume 137 | |
| 504 | |a Includes bibliographical references and index. | ||
| 588 | 0 | |a Online resource; title from PDF title page (SpringerLink, viewed December 4, 2018). | |
| 505 | 0 | |a Introduction -- Part I Black-Box Optimization -- 1 Nonlinear Optimization -- 2 Smooth Convex Optimization -- 3 Nonsmooth Convex Optimization -- 4 Second-Order Methods -- Part II Structural Optimization -- 5 Polynomial-time Interior-Point Methods -- 6 Primal-Dual Model of Objective Function -- 7 Optimization in Relative Scale -- Bibliographical Comments -- Appendix A. Solving some Auxiliary Optimization Problems -- References -- Index. | |
| 520 | |a 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.-- |c Provided by publisher. | ||
| 650 | 0 | |a Mathematical optimization. |0 http://id.loc.gov/authorities/subjects/sh85082127 | |
| 650 | 7 | |a Algorithms & data structures. |2 bicssc | |
| 650 | 7 | |a Numerical analysis. |2 bicssc | |
| 650 | 7 | |a Optimization. |2 bicssc | |
| 650 | 7 | |a Computers |x Programming |x Algorithms. |2 bisacsh | |
| 650 | 7 | |a Mathematics |x Applied. |2 bisacsh | |
| 650 | 7 | |a Mathematical optimization. |2 fast |0 (OCoLC)fst01012099 | |
| 655 | 0 | |a Electronic books. | |
| 655 | 4 | |a Electronic books. | |
| 773 | 0 | |t Springer eBooks | |
| 776 | 0 | 8 | |i Printed edition: |z 9783319915777 |
| 776 | 0 | 8 | |i Printed edition: |z 9783319915791 |
| 830 | 0 | |a Springer optimization and its applications ; |v v. 137. |x 1931-6828 |0 http://id.loc.gov/authorities/names/no2006059964 | |
| 903 | |a HeVa | ||
| 929 | |a oclccm | ||
| 999 | f | f | |i 949dc56b-4b0e-5b89-9c4a-1e4356838877 |s 8b3e104f-951a-51e7-acf4-6b252d575a73 |
| 928 | |t Library of Congress classification |a QA402.5 |l Online |c UC-FullText |u https://link.springer.com/10.1007/978-3-319-91578-4 |z Springer Nature |g ebooks |i 12558673 | ||