# Finding Nearest Neighbors in graphs locally

## TL;DR

This paper introduces a distributed algorithm for finding nearest neighbors in large graphs efficiently by local exploration, avoiding full graph traversal, and proves its convergence.

## Contribution

It presents a novel distributed local search algorithm for nearest neighbor discovery in graphs, scalable to large datasets.

## Key findings

- Algorithm converges reliably.
- Scalable to large graphs.
- Avoids full graph traversal.

## Abstract

Many distributed learning techniques have been motivated by the increasing size of datasets and their inability to fit into main memory on a single machine. We propose an algorithm that finds the nearest neighbor in a graph locally without the need of visiting the whole graph. Our algorithm is distributed which further encourage scalability. We prove the convergence of the algorithm