Reliable Distributed Clustering with Redundant Data Assignment
Distributed, Parallel, and Cluster Computing
2020-03-17 v1 Data Structures and Algorithms
Information Theory
Machine Learning
math.IT
Abstract
In this paper, we present distributed generalized clustering algorithms that can handle large scale data across multiple machines in spite of straggling or unreliable machines. We propose a novel data assignment scheme that enables us to obtain global information about the entire data even when some machines fail to respond with the results of the assigned local computations. The assignment scheme leads to distributed algorithms with good approximation guarantees for a variety of clustering and dimensionality reduction problems.
Cite
@article{arxiv.2002.08892,
title = {Reliable Distributed Clustering with Redundant Data Assignment},
author = {Venkata Gandikota and Arya Mazumdar and Ankit Singh Rawat},
journal= {arXiv preprint arXiv:2002.08892},
year = {2020}
}