Please use this identifier to cite or link to this item: http://hdl.handle.net/2440/58793
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Type: Conference paper
Title: Reconstructing Data Perturbed by Random Projections When the Mixing Matrix Is Known
Author: Sang, Y.
Shen, H.
Tian, H.
Citation: Machine Learning and Knowledge Discovery in Databases: European Conference, ECML PKDD 2009 Bled, Slovenia, September 7-11, 2009: Proceedings, Part II / W. Buntine, M. Grobelnik D. Mladenic, J. Shawe-Taylor (eds.): pp.334-349
Publisher: Springer
Publisher Place: Germany
Issue Date: 2009
Series/Report no.: Lecture Notes in Artificial Intelligence; 5782
ISBN: 3642041736
9783642041730
ISSN: 0302-9743
1611-3349
Conference Name: ECML/PKDD (2009 : Bled, Slovenia)
Statement of
Responsibility: 
Yingpeng Sang, Hong Shen and Hui Tian
Keywords: Privacy-preserving Data Mining; Data Perturbation; Data Reconstruction; Underdetermined Independent Component Analysis; Maximum A Posteriori; Principle Component Analysis
Rights: © Springer-Verlag Berlin Heidelberg 2009
RMID: 0020097490
DOI: 10.1007/978-3-642-04174-7_22
Appears in Collections:Computer Science publications

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