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CATEGORIES:Machine Learning Reading Group @ CUED
SUMMARY:An Introduction to the Conjugate Gradient Method -
Jihao Andeas Lin\, University of Cambridge
DTSTART;TZID=Europe/London:20240313T110000
DTEND;TZID=Europe/London:20240313T123000
UID:TALK213232AThttp://talks.cam.ac.uk
URL:http://talks.cam.ac.uk/talk/index/213232
DESCRIPTION:(Taken from: An Introduction to the Conjugate Grad
ient Method Without the Agonizing Pain\, Jonathan
Richard Shewchuk. Andy will walk us through this a
rticle.)\n\nThe Conjugate Gradient Method is the m
ost prominent iterative method for solving sparse
systems of linear equations. Unfortunately\, many
textbook treatments of the topic are written with
neither illustrations nor intuition\, and their vi
ctims can be found to this day babbling senselessl
y in the corners of dusty libraries. For this reas
on\, a deep\, geometric understanding of the metho
d has been reserved for the elite brilliant few wh
o have painstakingly decoded the mumblings of thei
r forebears. Nevertheless\, the Conjugate Gradient
Method is a composite of simple\, elegant ideas t
hat almost anyone can understand. Of course\, a re
ader as intelligent as yourself will learn them al
most effortlessly.\n\nThe idea of quadratic forms
is introduced and used to derive the methods of St
eepest Descent\, Conjugate Directions\, and Conjug
ate Gradients. Eigenvectors are explained and used
to examine the convergence of the Jacobi Method\,
Steepest Descent\, and Conjugate Gradients. Other
topics include preconditioning and the nonlinear
Conjugate Gradient Method. I have taken pains to m
ake this article easy to read. Sixty-six illustrat
ions are provided. Dense prose is avoided. Concept
s are explained in several different ways. Most eq
uations are coupled with an intuitive interpretati
on.\n \nReading recommendations: https://www.cs.cm
u.edu/~quake-papers/painless-conjugate-gradient.pd
f
LOCATION:Cambridge University Engineering Department\, CBL
Seminar room BE4-38.
CONTACT:Isaac Reid
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