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JMLR
2006
148views more  JMLR 2006»
14 years 9 months ago
Computational and Theoretical Analysis of Null Space and Orthogonal Linear Discriminant Analysis
Dimensionality reduction is an important pre-processing step in many applications. Linear discriminant analysis (LDA) is a classical statistical approach for supervised dimensiona...
Jieping Ye, Tao Xiong
NIPS
1997
14 years 11 months ago
EM Algorithms for PCA and SPCA
I present an expectation-maximization (EM) algorithm for principal component analysis (PCA). The algorithm allows a few eigenvectors and eigenvalues to be extracted from large col...
Sam T. Roweis
JMLR
2010
132views more  JMLR 2010»
14 years 4 months ago
Learning Gradients: Predictive Models that Infer Geometry and Statistical Dependence
The problems of dimension reduction and inference of statistical dependence are addressed by the modeling framework of learning gradients. The models we propose hold for Euclidean...
Qiang Wu, Justin Guinney, Mauro Maggioni, Sayan Mu...
CVPR
2001
IEEE
15 years 11 months ago
Combining Two-view Constraints For Motion Estimation
In this paper we describe two methods for estimating the motion parameters of an image sequence. For a sequence of images, the global motion can be described by ???? independent m...
Venu Madhav Govindu
TSP
2008
92views more  TSP 2008»
14 years 9 months ago
Quickest Detection and Tracking of Spawning Targets Using Monopulse Radar Channel Signals
Recent advances have been reported in detecting and estimating the location of more than one target within a single monopulse radar beam. Successful tracking of those targets has ...
Atef Isaac, Peter Willett, Yaakov Bar-Shalom