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  • Numerical Optimization (Springer Series in Operations Research and...
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Customer reviews

4.6 out of 5 stars
4.6 out of 5
107 global ratings
5 star
79%
4 star
12%
3 star
2%
2 star 0% (0%)
0%
1 star
7%
Numerical Optimization (Springer Series in Operations Research and Financial Engineering)

Numerical Optimization (Springer Series in Operations Research and Financial Engineering)

byJorge Nocedal
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107 total ratings, 34 with reviews

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From Canada

Amazon Customer
4.0 out of 5 stars Four Stars
Reviewed in Canada 🇨🇦 on June 5, 2016
Verified Purchase
Very nice book. It was in a very nice condition!
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Issoufou
5.0 out of 5 stars Five Stars
Reviewed in Canada 🇨🇦 on September 30, 2016
Verified Purchase
good
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From other countries

Bram
5.0 out of 5 stars Fantastic Book
Reviewed in the United States 🇺🇸 on March 19, 2021
Verified Purchase
This is a must-read book for anyone who wishes to study Numerical Analysis on a professional level. This text will teach many fundamental principals of applied analysis by walking the reader through an extremely wide array of finite dimensional optimization algorithms.
3 people found this helpful
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Prof. Dr. Ottmar Beucher
5.0 out of 5 stars Hervorragendes Buch
Reviewed in Germany 🇩🇪 on December 29, 2015
Verified Purchase
An der sicherlich nicht negativ gemeinten Kundenbewertung von Minh Duc Hoang erkennt man mal wieder den
kompletten Unfug, den die blödsinnige Sternebewertung darstellt (leider kann man sie ja beim
Schreiben einer Rezension nicht umgehen). Hier wird nicht
der Inhalt, sondern die Lieferung bewertet. Das ist sicherlich das gute Recht eines Rezensenten
und deshalb überhaupt kein Vorwurf an Minh Duc Hoang! Der Fehler liegt bei Amazon!!

Nach außen sind erstmal nur die drei Sterne zu sehen und kein Mensch weiß
zunächst, dass gar nicht der Inhalt rezensiert wurde.
Ich hoffe, dass irgendwann einmal jemand diesen Sterne-Mist abstellt!

Drei Sterne für so ein hervorragendes Buch?

Es hätte 30 Sterne verdient! Ich habe selten so ein verständlich geschriebenes und zugleich doch
tiefgehendes Buch gelesen. Hier geht es wirklich darum, dem Leser zunächst die Ideen zu vermitteln,
bevor die Details der Beweise diskutiert werden. So sollte ein Mathematik-Buch sein!
8 people found this helpful
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John Thingstad
5.0 out of 5 stars ... went into applied math and computer science I thoroughly enjoy this book
Reviewed in the United States 🇺🇸 on July 19, 2017
Verified Purchase
Trained a physicist before I went into applied math and computer science I thoroughly enjoy this book. It math is not light but not that heavy either. I wouldn't consider it math at graduate level as most of the material is applicable to an undergrad with 1 year of calculus and another of linear algebra. A bit more of statistical elaborations might be useful for a third edition, given the current focus on machine learning. Anyhow as a first book it is still excellent.
12 people found this helpful
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Vince
5.0 out of 5 stars Covers a lot of subjects nicely
Reviewed in Australia 🇦🇺 on December 1, 2020
Verified Purchase
Wonderful book .. I used it while completing a course. The book covers a wide domain of subjects and it is useful as a self study as well .. if you have the right background and interest of course.
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Amazon Customer
4.0 out of 5 stars detailed (enough) proofs for the material presented and a good balance between examples and theory
Reviewed in the United States 🇺🇸 on June 10, 2017
Verified Purchase
Not the easiest to read at times but a classic, solid math and algorithms book. Comprehensive appendix for the math used, detailed (enough) proofs for the material presented and a good balance between examples and theory.
2 people found this helpful
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Manchor Ko
5.0 out of 5 stars a classic
Reviewed in the United States 🇺🇸 on June 17, 2014
Verified Purchase
The best text book on the various issues around steepest descent, conjugate gradient, Newtonian methods etc. Clearly show you why you still need to care about steepest-descent even though we were taught it is much slower than Newton or CG. Those that are practical oriented might have ignored the key role SD play in many methods to guarantee convergence (or progress).

Very good write up on the Wolfe condition, Cauchy point, and trust region.
2 people found this helpful
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A. Chehade
5.0 out of 5 stars Great for Optimization People
Reviewed in the United States 🇺🇸 on January 5, 2016
Verified Purchase
This book is essential for any optimization guy. Provides most of the available methods including: stochastic gradient, steepest descent, newtons, trust-region methodologies.

One of the authors was my professor. So, I am biased toward the quality and the material in this book. Because, indeed the author would deliver the material in a much nicer way than others.
3 people found this helpful
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Ronan K.
5.0 out of 5 stars Very practical book on optimization.
Reviewed in the United States 🇺🇸 on March 23, 2019
Verified Purchase
This book is the best reference on the different optimization algorithms in use today. It is a very practical book and I find myself referring to it often.
One person found this helpful
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