A Network Compatibility Condition for Compressed Sensing over Complex Networks
Loading...
Access rights
openAccess
acceptedVersion
URL
Journal Title
Journal ISSN
Volume Title
A4 Artikkeli konferenssijulkaisussa
This publication is imported from Aalto University research portal.
View publication in the Research portal (opens in new window)
View/Open full text file from the Research portal (opens in new window)
Other link related to publication (opens in new window)
View publication in the Research portal (opens in new window)
View/Open full text file from the Research portal (opens in new window)
Other link related to publication (opens in new window)
Authors
Date
2018-08-29
Department
Major/Subject
Mcode
Degree programme
Language
en
Pages
5
Series
2018 IEEE Statistical Signal Processing Workshop, SSP 2018, pp. 50-54
Abstract
This paper continues our recently initiated line of work on analyzing the network Lasso (nLasso, which has been proposed as an efficient learning algorithm for massive networkstructured data sets (big data over networks). The nLasso extends the well-known Lasso estimator to network-structured datasets. In this paper we consider the nLasso using squared error loss and provide sufficient conditions on the network structure and available label information such that nLasso accurately recovers a clustered (piece-wise constant) graph signal (representing label information) from the information pro-vided by the labels of a few data points.Description
Keywords
big data over networks, complex networks, compressed sensing, network compatibility condition, network Lasso
Other note
Citation
Tran, N, Ambos, H & Jung, A 2018, A Network Compatibility Condition for Compressed Sensing over Complex Networks. in 2018 IEEE Statistical Signal Processing Workshop, SSP 2018., 8450811, IEEE, pp. 50-54, IEEE Statistical Signal Processing Workshop, Freiburg im Breisgau, Germany, 10/06/2018. https://doi.org/10.1109/SSP.2018.8450811