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» Learning Gaussian processes from multiple tasks
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ICIC
2005
Springer
15 years 8 months ago
Sequential Stratified Sampling Belief Propagation for Multiple Targets Tracking
Rather than the difficulties of highly non-linear and non-Gaussian observation process and the state distribution in single target tracking, the presence of a large, varying number...
Jianru Xue, Nanning Zheng, Xiaopin Zhong
ICASSP
2010
IEEE
15 years 1 months ago
A signal-specific bound for joint tdoa and FDOA estimation and its Use in combining multiple segments
We consider passive joint estimation of the time-difference of arrival (TDOA) and frequency-difference of arrival (FDOA) of an unknown signal at two sensors. The classical approac...
Arie Yeredor
ICRA
2007
IEEE
155views Robotics» more  ICRA 2007»
15 years 9 months ago
Value Function Approximation on Non-Linear Manifolds for Robot Motor Control
— The least squares approach works efficiently in value function approximation, given appropriate basis functions. Because of its smoothness, the Gaussian kernel is a popular an...
Masashi Sugiyama, Hirotaka Hachiya, Christopher To...
ICDM
2008
IEEE
193views Data Mining» more  ICDM 2008»
15 years 9 months ago
Multiplicative Mixture Models for Overlapping Clustering
The problem of overlapping clustering, where a point is allowed to belong to multiple clusters, is becoming increasingly important in a variety of applications. In this paper, we ...
Qiang Fu, Arindam Banerjee
124
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ICML
2006
IEEE
16 years 4 months ago
Nonstationary kernel combination
The power and popularity of kernel methods stem in part from their ability to handle diverse forms of structured inputs, including vectors, graphs and strings. Recently, several m...
Darrin P. Lewis, Tony Jebara, William Stafford Nob...