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: ShangHua 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 WellShaped Meshes and Nearest Neighbor Graphs Turner’s Theorem for Bandwidth of SemiRandom 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  WorstCase 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 