TCC
2012
Springer
12 years 2 months ago
2012
Springer
In this paper we study the problem of approximately releasing the cut function of a graph while preserving differential privacy, and give new algorithms (and new analyses of exis...
SIAMJO
2011
12 years 9 months ago
2011
Suppose we are given a matrix that is formed by adding an unknown sparse matrix to an unknown low-rank matrix. Our goal is to decompose the given matrix into its sparse and low-ran...
CORR
2010
Springer
13 years 5 months ago
2010
Springer
Singular Value Decomposition (and Principal Component Analysis) is one of the most widely used techniques for dimensionality reduction: successful and efficiently computable, it ...
TKDE
2008
13 years 6 months ago
2008
Matrix decomposition methods represent a data matrix as a product of two smaller matrices: one containing basis vectors that represent meaningful concepts in the data, and another ...