In pursuit of novelty: A decentralized approach to subspace clustering

Abstract

This paper considers the subspace clustering problem in a decentralized setting. The core algorithm finds directions of novelty in the span of the data to identify the membership of a collection of distributed data points. The low rank structure of the full M<inf>1</inf> &#x00D7; M<inf>2</inf> data matrix D is exploited to substantially reduce the… (More)
DOI: 10.1109/ALLERTON.2016.7852265

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Cite this paper

@article{Rahmani2016InPO, title={In pursuit of novelty: A decentralized approach to subspace clustering}, author={Mostafa Rahmani and George K. Atia}, journal={2016 54th Annual Allerton Conference on Communication, Control, and Computing (Allerton)}, year={2016}, pages={447-451} }