Luong, V. H., Deligiannis, N., Forchhammer, S., & Kaup, A. (2018). Online decomposition of compressive streaming data using n-l1 cluster-weighted minimization. In Data Compression Conference: DCC (pp. 1-10)

@inproceedings{9a11bee9b55348838e9f33f9460e2061,
title = "Online decomposition of compressive streaming data using n-l1 cluster-weighted minimization",
abstract = "We consider a decomposition method for compressive streaming data in the context ofonline compressive Robust Principle Component Analysis (RPCA). The proposed decompositionsolves an n-L1 cluster-weighted minimization to decompose a sequence of frames(or vectors), into sparse and low-rank components, from compressive measurements. Ourmethod processes a data vector of the stream per time instance from a small number ofmeasurements in contrast to conventional batch RPCA, which needs to access full data.The n-L1 cluster-weighted minimization leverages the sparse components along with theircorrelations with multiple previously-recovered sparse vectors. Moreover, the proposed minimizationcan exploit the structures of sparse components via clustering and re-weightingiteratively. The method outperforms the existing methods for both numerical data andactual video data.",
author = "Luong, {Van Huynh} and Nikolaos Deligiannis and S{\o}ren Forchhammer and Andr{\'e} Kaup",
year = "2018",
language = "English",
pages = "1--10",
booktitle = "Data Compression Conference",
}