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IJCV
2000
133views more  IJCV 2000»
13 years 7 months ago
Heteroscedastic Regression in Computer Vision: Problems with Bilinear Constraint
We present an algorithm to estimate the parameters of a linear model in the presence of heteroscedastic noise, i.e., each data point having a different covariance matrix. The algor...
Yoram Leedan, Peter Meer
CVPR
2005
IEEE
14 years 9 months ago
Robust L1 Norm Factorization in the Presence of Outliers and Missing Data by Alternative Convex Programming
Matrix factorization has many applications in computer vision. Singular Value Decomposition (SVD) is the standard algorithm for factorization. When there are outliers and missing ...
Qifa Ke, Takeo Kanade
SDM
2011
SIAM
414views Data Mining» more  SDM 2011»
12 years 10 months ago
Clustered low rank approximation of graphs in information science applications
In this paper we present a fast and accurate procedure called clustered low rank matrix approximation for massive graphs. The procedure involves a fast clustering of the graph and...
Berkant Savas, Inderjit S. Dhillon
VTC
2007
IEEE
104views Communications» more  VTC 2007»
14 years 1 months ago
Subspace Tracking Based Blind MIMO Transmit Preprocessing
Abstract— In this contribution projection approximation subspace tracking using deflation (PASTD) is investigated in the context of MIMO transmit preprocessing systems by exploi...
Wei Liu, Lie-Liang Yang, Lajos Hanzo
KDD
2004
ACM
124views Data Mining» more  KDD 2004»
14 years 8 months ago
Eigenspace-based anomaly detection in computer systems
We report on an automated runtime anomaly detection method at the application layer of multi-node computer systems. Although several network management systems are available in th...
Hisashi Kashima, Tsuyoshi Idé