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CS232

CS232. Schedule. 1. Introduction 2. Points vs vector (distance, balls, sphere) Chapter 1 3. Divide and Conquer: Algorithms for Near Neighbor Problem Handout (section). 4. Hyperplanes Chapter 2. Ray intersections Lines By linear equations By two points

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CS232

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  1. CS232

  2. Schedule • 1. Introduction • 2. Points vs vector (distance, balls, sphere) • Chapter 1 • 3. Divide and Conquer: Algorithms for Near Neighbor Problem • Handout (section)

  3. 4. HyperplanesChapter 2 • Ray intersections • Lines • By linear equations • By two points • When does a line passing the origin • Intersection of two lines • Matrix and algebraic approach (two variables and two equations)

  4. 3D • Ray and mirrors • Planes in three dimensions • By linear equations • By three points • When does a plane passing the origin

  5. Hyperplanes • Intersection of three planes • Matrix and algebraic approach (three variables and equations) • Hypereplanes in n-dimensions • By linear equations • By n points • When does a hyperplane passing through the origin • Intersection of n hyperplanes in n dimensions

  6. Matrix Form • What is a matrix? • Matrix vector multiplication • (inner product after all) • Matrix form of intersection of n hyperplanes --- system of linear equations?

  7. Column Picture: combination of vectors • Find proper linear combinations of vectors • Visualize hyperplane is hard, so you might eventually like the column pictures.

  8. Repeated the questions • Row pictures: n hyperplanes meets at a single points • Column pictures: combines n vectors to produce another vector

  9. Gaussian Elimination • Gaussian Elimination in 2 dimensions • example • Pictures • Pivots • Multipliers • Upper triangular matrix • Back substitution

  10. Two dimensions • Unique solution • No solution • Infinitely many solutions • What if the pivot is 0!!!

  11. 3D • Gaussian Elimination in 3 dimensions • example • Pictures • Pivots • Multipliers • Upper triangular matrix • Back substitution • Can be extended to any dimensions

  12. 5. Gaussian Elimination(General form) • Matrix Algebra • Matrix addition • Scalar times a matrix • Matrix multiplication • (dimensions have to agree) • Associative law • Non commutative law

  13. Gaussian Elimination(General form) • Identity matrix • Elimination matrix

  14. Permutation Matrix

  15. Matrix algebra(General form) • All the laws (page 58 – 59)

  16. Complexity of Matrix Multiplication • cube

  17. Block Multiplication

  18. Strassen’s Fast Matrix Mulplication • Divide and conquer

  19. 6. Inverse Matrix7 Quiz 18 LU factorization • Rest of chapter 2

  20. 9. Two dimensional convex Hull • From the handout • Convex combination

  21. 10. Algorithms for Null space • 3.1 – 3.3

  22. 11. Complete Linear Solver • 3.4 – 3.6

  23. 12. No class13 Geometric Projection • 4.1 – 4.2

  24. 14. Midterm15 Least Square Algorithm

  25. 16. QR Decomposition

  26. 17-18 no classes spring break

  27. 19. Hubs and AuthorityTheory for WebsHand out • Understanding webs • How Google works

  28. 20. Simplex and its Volume • Chapter 5

  29. 21. Determinants: Matrix Representation of volume

  30. 22. Eivenvalue problem and Spectral Geometry

  31. 23. Quiz 2

  32. 24. Diagonalization

  33. 25. Quadratic Shapes • Positive Definite matrices

  34. 26. Dimensional Reduction • Singular value Decomposition

  35. 27. Application: Computer Graphics

  36. 28. Spherical Geometry • Points on sphere • Caps • Stereographic Transformation

  37. 29. Geometric Transformation • Chapter 7

  38. 30 Geometric Transformation

  39. 31. Triangulations and Voronoi Diagram

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