Numerical Algorithms: Methods for Computer Vision, Machine Learning, and Graphics presents a new approach to numerical analysis for modern computer scientists. Using examples from a broad base of computational tasks, including data processing, computational photography, and animation, the textbook introduces numerical modeling and algorithmic desig

part |2 pages

Section I: Preliminaries

chapter 1|24 pages

Mathematics Review

chapter 2|18 pages

Numerics and Error Analysis

part |2 pages

Section II: Linear Algebra

chapter 3|18 pages

Linear Systems and the LU Decomposition

chapter 4|26 pages

Designing and Analyzing Linear Systems

chapter 5|16 pages

Column Spaces and QR

chapter 6|24 pages


chapter 7|14 pages

Singular Value Decomposition

part |2 pages

Section III: Nonlinear Techniques

chapter 8|16 pages

Nonlinear Systems

chapter 9|22 pages

Unconstrained Optimization

chapter 10|22 pages

Constrained Optimization

chapter 11|20 pages

Iterative Linear Solvers

chapter 12|28 pages

Specialized Optimization Methods

part |2 pages

Section IV: Functions, Derivatives, and Integrals

chapter 13|20 pages


chapter 14|26 pages

Integration and Differentiation

chapter 15|26 pages

Ordinary Differential Equations

chapter 16|32 pages

Partial Differential Equations