Detecting the dimension of the subspace correlated across multiple data sets in the sample poor regime
T. Hasija, Y. Song, P.J. Schreier, D. Ramírez, in: Proc.\ IEEE Work.\ Stat.\ Signal Process., Palma de Mallorca, Spain, 2016.
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Hasija, TanujLibreCat;
Song, Yang;
Schreier, Peter J.;
Ramírez, David
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Proc.\ IEEE Work.\ Stat.\ Signal Process.
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Hasija T, Song Y, Schreier PJ, Ramírez D. Detecting the dimension of the subspace correlated across multiple data sets in the sample poor regime. In: Proc.\ IEEE Work.\ Stat.\ Signal Process. ; 2016.
Hasija, T., Song, Y., Schreier, P. J., & Ramírez, D. (2016). Detecting the dimension of the subspace correlated across multiple data sets in the sample poor regime. Proc.\ IEEE Work.\ Stat.\ Signal Process.
@inproceedings{Hasija_Song_Schreier_Ramírez_2016, place={Palma de Mallorca, Spain}, title={Detecting the dimension of the subspace correlated across multiple data sets in the sample poor regime}, booktitle={Proc.\ IEEE Work.\ Stat.\ Signal Process.}, author={Hasija, Tanuj and Song, Yang and Schreier, Peter J. and Ramírez, David}, year={2016} }
Hasija, Tanuj, Yang Song, Peter J. Schreier, and David Ramírez. “Detecting the Dimension of the Subspace Correlated across Multiple Data Sets in the Sample Poor Regime.” In Proc.\ IEEE Work.\ Stat.\ Signal Process. Palma de Mallorca, Spain, 2016.
T. Hasija, Y. Song, P. J. Schreier, and D. Ramírez, “Detecting the dimension of the subspace correlated across multiple data sets in the sample poor regime,” 2016.
Hasija, Tanuj, et al. “Detecting the Dimension of the Subspace Correlated across Multiple Data Sets in the Sample Poor Regime.” Proc.\ IEEE Work.\ Stat.\ Signal Process., 2016.
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