TY - GEN
T1 - Reliable Distributed Clustering with Redundant Data Assignment
AU - Gandikota, Venkata
AU - Mazumdar, Arya
AU - Rawat, Ankit Singh
N1 - Publisher Copyright:
© 2020 IEEE.
PY - 2020/6
Y1 - 2020/6
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=85090415806&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85090415806&partnerID=8YFLogxK
U2 - 10.1109/ISIT44484.2020.9174299
DO - 10.1109/ISIT44484.2020.9174299
M3 - Conference contribution
AN - SCOPUS:85090415806
T3 - IEEE International Symposium on Information Theory - Proceedings
SP - 2556
EP - 2561
BT - 2020 IEEE International Symposium on Information Theory, ISIT 2020 - Proceedings
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2020 IEEE International Symposium on Information Theory, ISIT 2020
Y2 - 21 July 2020 through 26 July 2020
ER -