On a generalization of iterated and randomized rounding

11/05/2018
by   Nikhil Bansal, et al.
0

We give a general method for rounding linear programs that combines the commonly used iterated rounding and randomized rounding techniques. In particular, we show that whenever iterated rounding can be applied to a problem with some slack, there is a randomized procedure that returns an integral solution that satisfies the guarantees of iterated rounding and also has concentration properties. We use this to give new results for several classic problems where iterated rounding has been useful.

READ FULL TEXT

page 1

page 2

page 3

page 4

research
06/01/2020

Randomized Kaczmarz for Tensor Linear Systems

Solving linear systems of equations is a fundamental problem in mathemat...
research
08/29/2023

Randomized Quasi Polynomial Algorithm for Subset-Sum Problems with At Most One Solution

In this paper we study the Subset Sum Problem (SSP). Assuming the SSP ha...
research
08/02/2020

Concentration-Bound Analysis for Probabilistic Programs and Probabilistic Recurrence Relations

Analyzing probabilistic programs and randomized algorithms are classical...
research
10/02/2022

Error estimates of Kaczmarz and randomized Kaczmarz methods

The Kaczmarz method is an iterative projection scheme for solving con-si...
research
03/04/2020

Notes on Randomized Algorithms

Lecture notes for the Yale Computer Science course CPSC 469/569 Randomiz...
research
01/20/2018

Probabilistic Tools for the Analysis of Randomized Optimization Heuristics

This chapter collects several probabilistic tools that proved to be usef...
research
04/04/2022

Randomized Block Adaptive Linear System Solvers

Randomized linear solvers leverage randomization to structure-blindly co...

Please sign up or login with your details

Forgot password? Click here to reset