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

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

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

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Book Details:

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Category
Year:2016
Publisher:Autoedición
Pages:351 pages
Language:english
Since:07/07/2016
Size:4.18 MB
License:CC-BY

Content:

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

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