Analysis of Kelner and Levin graph sparsification algorithm for a streaming setting

09/13/2016
by   Daniele Calandriello, et al.
0

We derive a new proof to show that the incremental resparsification algorithm proposed by Kelner and Levin (2013) produces a spectral sparsifier in high probability. We rigorously take into account the dependencies across subsequent resparsifications using martingale inequalities, fixing a flaw in the original analysis.

READ FULL TEXT

page 1

page 2

page 3

page 4

research
12/04/2020

An O(n) time algorithm for finding Hamilton cycles with high probability

We design a randomized algorithm that finds a Hamilton cycle in 𝒪(n) tim...
research
06/21/2023

Rényi–Sobolev Inequalities and Connections to Spectral Graph Theory

In this paper, we generalize the log-Sobolev inequalities to Rényi–Sobol...
research
05/13/2014

Rate of Convergence and Error Bounds for LSTD(λ)

We consider LSTD(λ), the least-squares temporal-difference algorithm wit...
research
07/20/2023

Quantum Logspace Computations are Verifiable

In this note, we observe that quantum logspace computations are verifiab...
research
01/31/2018

Incremental kernel PCA and the Nyström method

Incremental versions of batch algorithms are often desired, for increase...
research
12/19/2022

The One-Inclusion Graph Algorithm is not Always Optimal

The one-inclusion graph algorithm of Haussler, Littlestone, and Warmuth ...
research
10/01/2020

StreamSoNG: A Soft Streaming Classification Approach

Examining most streaming clustering algorithms leads to the understandin...

Please sign up or login with your details

Forgot password? Click here to reset