Title
Reliable Distributed Clustering with Redundant Data Assignment
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.
Year
DOI
Venue
2020
10.1109/ISIT44484.2020.9174299
ISIT
DocType
Citations 
PageRank 
Conference
0
0.34
References 
Authors
0
3
Name
Order
Citations
PageRank
Venkata Gandikota154.46
Arya Mazumdar230741.81
Ankit Singh Rawat346533.94