| 1 |
Introduction |
EppBAP.mat (MAT) |
| 2 |
The Condition Number |
airfoil1.mat (MAT) |
| 3 |
The Largest Singular Value of a Matrix |
airfoil2.mat (MAT) |
| 4 |
Gaussian Elimination Without Pivoting |
art.m (M) |
| 5 |
Smoothed Analysis of Gaussian Elimination Without Pivoting |
art3.m (M) |
| 6 |
Growth Factors of Partial and Complete Pivoting
Speeding up GE of Graphs with Low Bandwidth or Small Separators |
chew_circle.mat (MAT)
convert.m (M) |
| 7 |
Spectral Partitioning Introduced |
crossedGrid.m (M) |
| 8 |
Spectral Partitioning of Planar Graphs |
dat.mat (MAT) |
| 9 |
Spectral Paritioning of Well-Shaped Meshes and Nearest Neighbor Graphs
Turner's Theorem for Bandwidth of Semi-Random Graphs |
epp.mat (MAT)
eppstein.mat (MAT) |
| 10 |
Smoothed Analysis and Monotone Adversaries for Bandwidth and Graph Bisection
McSherry's Spectral Bisection Algorithm |
fastfiedler.m (M)
gauss.m (M) |
| 11 |
Introduction to Linear Programming
von Neumann's Algorithm, Primal and Dual Simplex Methods
Duality |
graph2A.m (M)
kahan.m (M)
kahan2.m (M) |
| 12 |
Strong Duality Theorem of Linear Programming
Renegar's Condition Numbers |
laplacian.m (M)
mcrack.mat (MAT) |
| 13 |
Analysis of von Neumann's Algorithm |
n.mat (MAT) |
| 14 |
Worst-Case Complexity of the Implex Method |
noPivot.m (M) |
| 15 |
The Expected Number of Facets of the Convex Hull of Gaussian Random Points in the Plane |
ppConj.m (M) |
| 16 |
The Expected Number of Facets of the Convex Hull of Gaussian Random Points in the Plane (cont.) |
ppDat.mat (MAT) |
| 17 |
The Expected Number of Facets of the Shadow of a polytope Given by Gaussian random Constraints |
spectShow.m (M) |
| 18 |
The Expected Number of Facets of the Shadow of a Polytope Given by Gaussian Random Constraints: Distance Bound |
spectShow1.m (M) |
| 19 |
The Expected Number of Facets of the Shadow of a Polytope Given by Gaussian Random Constraints: Angle Bound and Overview of Phase 1 |
v4.mat (MAT) |