Students in this class were required to scribe lecture notes in order to gain experience writing mathematics. The lecture notes files are included courtesy the students listed below.
LEC # | TOPICS | LECTURE NOTES | SCRIBES / LECTURERS |
---|---|---|---|
1 | Introduction | ||
2 | The Condition Number | (PDF) (Courtesy of Steve Weis. Used with permission.) |
Scribe: Steve Weis Lecturer: Daniel Spielman |
3 | The Largest Singular Value of a Matrix | (PDF) (Courtesy of Arvind Sankar. Used with permission.) |
Scribe: Arvind Sankar Lecturer: Daniel Spielman |
4 | Gaussian Elimination Without Pivoting | (PDF) (Courtesy of Matthew Lepinski. Used with permission.) |
Scribe: Matthew Lepinski Lecturer: Daniel Spielman |
5 | Smoothed Analysis of Gaussian Elimination Without Pivoting | (PDF) (Courtesy of Nitin Thaper. Used with permission.) |
Scribe: Nitin Thaper Lecturer: Daniel Spielman |
6 |
Growth Factors of Partial and Complete Pivoting
Speeding up GE of Graphs with Low Bandwidth or Small Separators |
(PDF) (Courtesy of Brian Sutton. Used with permission.) |
Scribe: Brian Sutton Lecturer: Daniel Spielman |
7 | Spectral Partitioning Introduced | (PDF) (Courtesy of Michael Korn. Used with permission.) |
Scribe: Michael Korn Lecturer: Shang-Hua Teng |
8 | Spectral Partitioning of Planar Graphs | (PDF) (Courtesy of Jan Vondrák. Used with permission.) |
Scribe: Jan Vondrák Lecturer: Daniel Spielman |
9 |
Spectral Parititioning of Well-Shaped Meshes and Nearest Neighbor Graphs Turner’s Theorem for Bandwidth of Semi-Random Graphs |
(PDF) |
Scribe: Stephan Kalhamer Lecturer: Daniel Spielman |
10 |
Smoothed Analysis and Monotone Adversaries for Bandwidth and Graph Bisection McSherry’s Spectral Bisection Algorithm |
(PDF) | Lecturer: Daniel Spielman |
11 |
Introduction to Linear Programming von Neumann’s Algorithm, Primal and Dual Simplex Methods Duality |
(PDF) (Courtesy of José Correa. Used with permission.) |
Scribe: José Correa
Lecturer: Daniel Spielman |
12 |
Strong Duality Theorem of Linear Programming Renegar’s Condition Numbers |
(PDF) (Courtesy of Arvind Sankar. Used with permission.) |
Scribe: Arvind Sankar Lecturer: Daniel Spielman |
13 | Analysis of von Neumann’s Algorithm | (PDF) (Courtesy of Nitin Thaper. Used with permission.) |
Scribe: Nitin Thaper Lecturer: Daniel Spielman |
14 | Worst-Case Complexity of the Simplex Method | (PDF ) (Courtesy of Brian Sutton. Used with permission.) |
Scribe: Brian Sutton
Lecturer: Daniel Spielman |
15 | The Expected Number of Facets of the Convex Hull of Gaussian Random Points in the Plane | (PDF) |
Scribe: Mikhail Alekhnovitch Lecturer: Daniel Spielman |
16 | The Expected Number of Facets of the Convex Hull of Gaussian Random Points in the Plane (cont.) | (PDF) (Courtesy of Mikhail Alekhnovitch. Used with permission.) |
Scribe: Mikhail Alekhnovitch Lecturer: Daniel Spielman |
17 | The Expected Number of Facets of the Shadow of a Polytope Given by Gaussian Random Constraints | (PDF) (Courtesy of Steve Weis. Used with permission.) |
Scribe: Steve Weis Lecturer: Daniel Spielman |
18 | The Expected Number of Facets of the Shadow of a Polytope Given by Gaussian Random Constraints: Distance Bound |
Scribe: Stephan Kalhamer Lecturer: Daniel Spielman |
|
19 | The Expected Number of Facets of the Shadow of a Polytope Given by Gaussian Random Constraints: Angle Bound and Overview of Phase 1 | (PDF) (Courtesy of Matthew Lepinski. Used with permission.) |
Scribe: Matthew Lepinski Lecturer: Daniel Spielman |