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» Fast matrix rank algorithms and applications
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WWW
2005
ACM
15 years 10 months ago
TotalRank: ranking without damping
PageRank is defined as the stationary state of a Markov chain obtained by perturbing the transition matrix of a web graph with a damping factor that spreads part of the rank. The...
Paolo Boldi
ISCAS
2006
IEEE
112views Hardware» more  ISCAS 2006»
15 years 3 months ago
Differential and geometric properties of Rayleigh quotients with applications
the following cost functions: In this paper, learning rules are proposed for simultaneous corn- GI(U) = tr{(UTU)(UTBU)-lD, (la) putation of minor eigenvectors of a covariance matri...
M. A. Hasan
ICASSP
2009
IEEE
15 years 4 months ago
A fast asymptotically efficient algorithm for blind separation of a linear mixture of block-wise stationary autoregressive proce
We propose a novel blind source separation algorithm called Block AutoRegressive Blind Identification (BARBI). The algorithm is asymptotically efficient in separation of instant...
Petr Tichavský, Arie Yeredor, Zbynek Koldov...
SIAMJO
2011
14 years 4 months ago
Recovering Low-Rank and Sparse Components of Matrices from Incomplete and Noisy Observations
Many applications arising in a variety of fields can be well illustrated by the task of recovering the low-rank and sparse components of a given matrix. Recently, it is discovered...
Min Tao, Xiaoming Yuan
98
Voted
JCP
2008
171views more  JCP 2008»
14 years 9 months ago
Mining Frequent Subgraph by Incidence Matrix Normalization
Existing frequent subgraph mining algorithms can operate efficiently on graphs that are sparse, have vertices with low and bounded degrees, and contain welllabeled vertices and edg...
Jia Wu, Ling Chen