<--- Back to Details
First PageDocument Content
Mathematical analysis / Numerical analysis / Mathematics / Numerical linear algebra / Root-finding algorithms / Iterative refinement / Residual / Newton's method / Pi / Approximations of / Gradient descent / Mathematical optimization
Date: 2010-07-21 10:31:16
Mathematical analysis
Numerical analysis
Mathematics
Numerical linear algebra
Root-finding algorithms
Iterative refinement
Residual
Newton's method
Pi
Approximations of
Gradient descent
Mathematical optimization

What is iterative refinement How to use iterative refinement to verify a computed result? Influence of the computing precision Conclusion and future work Iterative refinement:

Add to Reading List

Source URL: www.lix.polytechnique.fr

Download Document from Source Website

File Size: 545,47 KB

Share Document on Facebook

Similar Documents

13  Numerical Linear Algebra We consider here the numerical side of linear algebra, the symbolic side being described in Chapter 8. The linear algebra numerical analysis and methods are discussed in [TBI97, Sch02]. The b

13 Numerical Linear Algebra We consider here the numerical side of linear algebra, the symbolic side being described in Chapter 8. The linear algebra numerical analysis and methods are discussed in [TBI97, Sch02]. The b

DocID: 1tLKo - View Document

NUMERICAL LINEAR ALGEBRA WITH APPLICATIONS Numer. Linear Algebra Appl. 2001; 00:1–6 Prepared using nlaauth.cls [Version: v1.0] Preconditioning KKT systems

NUMERICAL LINEAR ALGEBRA WITH APPLICATIONS Numer. Linear Algebra Appl. 2001; 00:1–6 Prepared using nlaauth.cls [Version: v1.0] Preconditioning KKT systems

DocID: 1t9SY - View Document

Assignment 3 Randomization in Numerical Linear Algebra (PCMI) 1. Let A be an n × d matrix with n  d. (i) Give an example of a matrix A whose row leverage scores are all equal. (ii) Give an example of a matrix A whose r

Assignment 3 Randomization in Numerical Linear Algebra (PCMI) 1. Let A be an n × d matrix with n  d. (i) Give an example of a matrix A whose row leverage scores are all equal. (ii) Give an example of a matrix A whose r

DocID: 1sv5W - View Document

Microsoft PowerPoint - lacsi-sans-1006

Microsoft PowerPoint - lacsi-sans-1006

DocID: 1ru2M - View Document

Time Series Lesson 9 Grant Foster  Representing Data

Time Series Lesson 9 Grant Foster Representing Data

DocID: 1rs99 - View Document