# Finding Many Sparse Cuts Using Entropy Maximization

arXiv: https://arxiv.org/abs/2203.07869 · HTML: https://mlsanity.com/paper/2203.07869/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 8 Mar 2022.

## Built on by (most cited first, 1 of 1)

- [A Bayesian Approach To Graph Partitioning](https://mlsanity.com/paper/2204.12927/) (2022)

## Abstract (arXiv)

A randomized algorithm for finding sparse cuts is given which is based on constructing a dual markov chain called multiscale rings process(MRP) and a new concept of entropy. It is shown how the time to absorption of the dual process measures the connectedness of the graph and mixing of the corresponding markov process which is then utilized to do clustering. The second algorithm uses the entropy which provides a new methodology and a set of tools to think about sparse cuts as well as sparsification of a graph.