We introduce the smoothed analysis of algorithms, which continuously interpolates between
the worst-case and average-case analyses of algorithms. In smoothed analysis, we measure …

The many facets of linear programming * Page 1 Mathematical Programming manuscript No.
(will be inserted by the editor) Michael J. Todd The many facets of linear programming * March …

In this paper the abstract of the thesis” New Interior Point Algorithms in Linear Programming”
is presented. The purpose of the thesis is to elaborate new interior point algorithms for …

Explaining the excellent practical performance of the simplex method for linear programming
has been a major topic of research for over 50 years. One of the most successful frameworks …

LNCS 3623 - The Smoothed Analysis of Algorithms Page 1 The Smoothed Analysis of Algorithms
Daniel A. Spielman Department of Mathematics, Massachusetts Institute of Technology …

The simplex algorithm is among the most widely used algorithms for solving linear programs
in practice. With essentially all deterministic pivoting rules it is known, however, to require an …

In the first part of the paper we survey some far-reaching applications of the basic facts of
linear programming to the combinatorial theory of simple polytopes. In the second part we …

Dependency parsing with high-order features results in a provably hard decoding problem.
A lot of work has gone into developing powerful optimization methods for solving these …

Neighborly cubical polytopes exist: for any n≥ d≥ 2r+ 2, there is a cubical convex d-
polytope C dn whose r-skeleton is combinatorially equivalent to that of the n-dimensional …

We show that the Simplex Method, the Network Simplex Method—both with Dantzig's
original pivot rule—and the Successive Shortest Path Algorithm are NP-mighty. That is, each …