Consensus clustering: The filtered stochastic best-one-element-move algorithm

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Scopus citations

Abstract

The consensus clustering problem is to find a clustering partition that has minimum average distance to a set of given partitions, generated from a number of different clustering algorithms or different runs of the same clustering algorithm. Different definitions of partition distance and different optimization methods lead to many consensus clustering algorithms. In this paper, a new algorithm is proposed for solving the median partition problem, combining the idea of the Best One Element Move (BOEM) algorithm and stochastic gradient descent (SGD) with a filtering step. Simulation results demonstrate that this new algorithm converges faster than the vanilla version of BOEM and performs competitively with other algorithms. Moreover, it sheds some light on how to use SGD methods in discrete domain problems, and on the efficacy of introducing memory in estimation of local gradients.

Original languageEnglish (US)
Title of host publication2011 45th Annual Conference on Information Sciences and Systems, CISS 2011
DOIs
StatePublished - Jun 6 2011
Event2011 45th Annual Conference on Information Sciences and Systems, CISS 2011 - Baltimore, MD, United States
Duration: Mar 23 2011Mar 25 2011

Publication series

Name2011 45th Annual Conference on Information Sciences and Systems, CISS 2011

Other

Other2011 45th Annual Conference on Information Sciences and Systems, CISS 2011
CountryUnited States
CityBaltimore, MD
Period3/23/113/25/11

All Science Journal Classification (ASJC) codes

  • Information Systems

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    Zheng, H., Kulkarni, S. R., & Poor, H. V. (2011). Consensus clustering: The filtered stochastic best-one-element-move algorithm. In 2011 45th Annual Conference on Information Sciences and Systems, CISS 2011 [5766165] (2011 45th Annual Conference on Information Sciences and Systems, CISS 2011). https://doi.org/10.1109/CISS.2011.5766165