Network flow theory has been used across a number of disciplines, including theoretical
computer science, operations research, and discrete math, to model not only problems in the …

Given a convex function $ f $ on $\mathbb {R}^ n $ with an integer minimizer, we show how
to find an exact minimizer of $ f $ using $ O (n^ 2\log n) $ calls to a separation oracle and …

The Forster transform is a method of regularizing a dataset by placing it in radial isotropic
position while maintaining some of its essential properties. Forster transforms have played a …

Given a separation oracle SO for a convex function f that has an integral minimizer inside a
box with radius R, we show how to efficiently find a minimizer of f using at most O (n (n+ log …

We present a strongly polynomial algorithm for computing an equilibrium in Arrow-Debreu
exchange markets with linear utilities. Our algorithm is based on a variant of the weakly …

In breakthrough work, Tardos (Oper. Res.'86) gave a proximity based framework for solving
linear programming (LP) in time depending only on the constraint matrix in the bit complexity …

Following the breakthrough work of Tardos (Oper. Res.'86) in the bit-complexity model,
Vavasis and Ye (Math. Prog.'96) gave the first exact algorithm for linear programming in the …

A strongly polynomial algorithm is given for the generalized flow maximization problem. It
uses a new variant of the scaling technique, called continuous scaling. The main measure of …

We consider two classical network flow problems. First, it is possible to store excess flow in
the intermediate nodes to improve the total amount of flow that can be transported through …

We present a connection between two dynamical systems arising in entirely different
contexts: the Iteratively Reweighted Least Squares (IRLS) algorithm used in compressed …