Labs for Foundations of Applied Mathematics Volume II: Algorithm Design and Optimization

This lab manual is designed to accompany the textbook Foundations of Applied Mathematics by Humpherys and Jarvis.

Contents:

• Standard Librar
• Object-Oriented Programming
• Data Structures
• Depth and Breadth-First Searching with Kevin Bacon
• Kruskal’s Algorithm
• Nearest Neighbor Search
• Pseudorandom Number Generators
• Statistical Distributions
• Regression
• Fast Fourier Transform
• Filtering and Convolution
• Fourier Transform Extensions
• Intro to Wavelets
• Floating Point Numbers
• Limitations of Floating Point Computation
• Barycentric Lagrange Interpolation
• Newton-Cotes Integration
• Polynomial Interpolation Using Chebyshev Polynomials
• scipy.optimize
• CVXOPT
• Simplex Method
• Line Search Algorithms
• Trust-Region Methods
• Conjugate-Gradient
• Interior Point I
• Interior Point II
• Compressed Sensing
• Value Function Iteration
• Policy Function Iteration
• Multi-Armed Bandit Problems