Language:
English
繁體中文
Help
Login
Back
Switch To:
Labeled
|
MARC Mode
|
ISBD
An introduction to optimization on smooth manifolds
Record Type:
Language materials, printed : Monograph/item
Title/Author:
An introduction to optimization on smooth manifolds/ Nicolas Boumal.
Author:
Boumal, Nicolas,
Published:
Cambridge ;Cambridge University Press, : 2023.,
Description:
xviii, 338 p. :ill., digital ; : 27 cm.;
Notes:
Title from publisher's bibliographic system (viewed on 09 Mar 2023).
Subject:
Manifolds (Mathematics) -
Online resource:
https://doi.org/10.1017/9781009166164
ISBN:
9781009166164
An introduction to optimization on smooth manifolds
Boumal, Nicolas,1987-
An introduction to optimization on smooth manifolds
[electronic resource] /Nicolas Boumal. - Cambridge ;Cambridge University Press,2023. - xviii, 338 p. :ill., digital ;27 cm.
Title from publisher's bibliographic system (viewed on 09 Mar 2023).
Simple examples -- Embedded geometry : first order -- First-order optimization algorithms -- Embedded geometry : second order -- Second-order optimization algorithms -- Embedded submanifolds : examples -- General manifolds -- Quotient manifolds -- Additional tools -- Geodesic convexity.
Optimization on Riemannian manifolds-the result of smooth geometry and optimization merging into one elegant modern framework-spans many areas of science and engineering, including machine learning, computer vision, signal processing, dynamical systems and scientific computing. This text introduces the differential geometry and Riemannian geometry concepts that will help students and researchers in applied mathematics, computer science and engineering gain a firm mathematical grounding to use these tools confidently in their research. Its charts-last approach will prove more intuitive from an optimizer's viewpoint, and all definitions and theorems are motivated to build time-tested optimization algorithms. Starting from first principles, the text goes on to cover current research on topics including worst-case complexity and geodesic convexity. Readers will appreciate the tricks of the trade for conducting research and for numerical implementations sprinkled throughout the book.
ISBN: 9781009166164Subjects--Topical Terms:
672402
Manifolds (Mathematics)
LC Class. No.: QA613 / .B68 2023
Dewey Class. No.: 516.36
An introduction to optimization on smooth manifolds
LDR
:02175nam a2200277 a 4500
001
1138021
003
UkCbUP
005
20230309021938.0
006
m d
007
cr nn 008maaau
008
250110s2023 enk o 1 0 eng d
020
$a
9781009166164
$q
(electronic bk.)
020
$a
9781009166171
$q
(hardback)
020
$a
9781009166157
$q
(paperback)
035
$a
CR9781009166164
040
$a
UkCbUP
$b
eng
$c
UkCbUP
$d
GP
041
0
$a
eng
050
0 0
$a
QA613
$b
.B68 2023
082
0 0
$a
516.36
$2
23
090
$a
QA613
$b
.B764 2023
100
1
$a
Boumal, Nicolas,
$d
1987-
$e
author.
$3
1446603
245
1 3
$a
An introduction to optimization on smooth manifolds
$h
[electronic resource] /
$c
Nicolas Boumal.
260
$a
Cambridge ;
$a
New York, NY :
$b
Cambridge University Press,
$c
2023.
300
$a
xviii, 338 p. :
$b
ill., digital ;
$c
27 cm.
500
$a
Title from publisher's bibliographic system (viewed on 09 Mar 2023).
505
0
$a
Simple examples -- Embedded geometry : first order -- First-order optimization algorithms -- Embedded geometry : second order -- Second-order optimization algorithms -- Embedded submanifolds : examples -- General manifolds -- Quotient manifolds -- Additional tools -- Geodesic convexity.
520
$a
Optimization on Riemannian manifolds-the result of smooth geometry and optimization merging into one elegant modern framework-spans many areas of science and engineering, including machine learning, computer vision, signal processing, dynamical systems and scientific computing. This text introduces the differential geometry and Riemannian geometry concepts that will help students and researchers in applied mathematics, computer science and engineering gain a firm mathematical grounding to use these tools confidently in their research. Its charts-last approach will prove more intuitive from an optimizer's viewpoint, and all definitions and theorems are motivated to build time-tested optimization algorithms. Starting from first principles, the text goes on to cover current research on topics including worst-case complexity and geodesic convexity. Readers will appreciate the tricks of the trade for conducting research and for numerical implementations sprinkled throughout the book.
650
0
$a
Manifolds (Mathematics)
$3
672402
650
0
$a
Mathematical optimization.
$3
527675
856
4 0
$u
https://doi.org/10.1017/9781009166164
based on 0 review(s)
Multimedia
Reviews
Add a review
and share your thoughts with other readers
Export
pickup library
Processing
...
Change password
Login
Please sign in
User name
Password
Remember me on this computer
Cancel
Forgot your password?