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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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Schedule • 1. Introduction • 2. Points vs vector (distance, balls, sphere) • Chapter 1 • 3. Divide and Conquer: Algorithms for Near Neighbor Problem • Handout (section)
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)
3D • Ray and mirrors • Planes in three dimensions • By linear equations • By three points • When does a plane passing the origin
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
Matrix Form • What is a matrix? • Matrix vector multiplication • (inner product after all) • Matrix form of intersection of n hyperplanes --- system of linear equations?
Column Picture: combination of vectors • Find proper linear combinations of vectors • Visualize hyperplane is hard, so you might eventually like the column pictures.
Repeated the questions • Row pictures: n hyperplanes meets at a single points • Column pictures: combines n vectors to produce another vector
Gaussian Elimination • Gaussian Elimination in 2 dimensions • example • Pictures • Pivots • Multipliers • Upper triangular matrix • Back substitution
Two dimensions • Unique solution • No solution • Infinitely many solutions • What if the pivot is 0!!!
3D • Gaussian Elimination in 3 dimensions • example • Pictures • Pivots • Multipliers • Upper triangular matrix • Back substitution • Can be extended to any dimensions
5. Gaussian Elimination(General form) • Matrix Algebra • Matrix addition • Scalar times a matrix • Matrix multiplication • (dimensions have to agree) • Associative law • Non commutative law
Gaussian Elimination(General form) • Identity matrix • Elimination matrix
Matrix algebra(General form) • All the laws (page 58 – 59)
Strassen’s Fast Matrix Mulplication • Divide and conquer
6. Inverse Matrix7 Quiz 18 LU factorization • Rest of chapter 2
9. Two dimensional convex Hull • From the handout • Convex combination
10. Algorithms for Null space • 3.1 – 3.3
11. Complete Linear Solver • 3.4 – 3.6
12. No class13 Geometric Projection • 4.1 – 4.2
19. Hubs and AuthorityTheory for WebsHand out • Understanding webs • How Google works
20. Simplex and its Volume • Chapter 5
25. Quadratic Shapes • Positive Definite matrices
26. Dimensional Reduction • Singular value Decomposition
28. Spherical Geometry • Points on sphere • Caps • Stereographic Transformation
29. Geometric Transformation • Chapter 7