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CVPR
2006
IEEE
14 years 10 months ago
Semi-Supervised Classification Using Linear Neighborhood Propagation
We consider the general problem of learning from both labeled and unlabeled data. Given a set of data points, only a few of them are labeled, and the remaining points are unlabele...
Fei Wang, Changshui Zhang, Helen C. Shen, Jingdong...
ICARCV
2008
IEEE
170views Robotics» more  ICARCV 2008»
14 years 2 months ago
Mixed state estimation for a linear Gaussian Markov model
— We consider a discrete-time dynamical system with Boolean and continuous states, with the continuous state propagating linearly in the continuous and Boolean state variables, a...
Argyris Zymnis, Stephen P. Boyd, Dimitry M. Gorine...
INFOVIS
2003
IEEE
14 years 1 months ago
Visualization of Labeled Data Using Linear Transformations
We present a novel family of data-driven linear transformations, aimed at visualizing multivariate data in a low-dimensional space in a way that optimally preserves the structure ...
Yehuda Koren, Liran Carmel
NN
2000
Springer
161views Neural Networks» more  NN 2000»
13 years 8 months ago
How good are support vector machines?
Support vector (SV) machines are useful tools to classify populations characterized by abrupt decreases in density functions. At least for one class of Gaussian data model the SV ...
Sarunas Raudys
CISS
2008
IEEE
14 years 2 months ago
A low complexity linear multiuser MIMO beamforming system with limited feedback
—In this paper, we propose a low complexity linear multiuser beamforming system for the multiple-input multipleoutput (MIMO) broadcast channel. We consider the specific case of ...
Chan-Byoung Chae, David Mazzarese, Nihar Jindal, R...