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NIPS
2004
13 years 11 months ago
Learning Gaussian Process Kernels via Hierarchical Bayes
We present a novel method for learning with Gaussian process regression in a hierarchical Bayesian framework. In a first step, kernel matrices on a fixed set of input points are l...
Anton Schwaighofer, Volker Tresp, Kai Yu
SODA
1997
ACM
171views Algorithms» more  SODA 1997»
13 years 11 months ago
A Practical Approximation Algorithm for the LMS Line Estimator
The problem of fitting a straight line to a finite collection of points in the plane is an important problem in statistical estimation. Robust estimators are widely used because...
David M. Mount, Nathan S. Netanyahu, Kathleen Roma...
ATAL
2006
Springer
14 years 1 months ago
Multi-model motion tracking under multiple team member actuators
Autonomous robots need to track objects. Object tracking relies on predefined robot motion and sensory models. Tracking is particularly challenging if the robots can actuate on th...
Yang Gu, Manuela M. Veloso
AVSS
2005
IEEE
14 years 3 months ago
Multiple object tracking using elastic matching
A novel region-based multiple object tracking framework based on Kalman filtering and elastic matching is proposed. The proposed Kalman filtering-elastic matching model is gener...
Xingzhi Luo, Suchendra M. Bhandarkar
ICIAR
2005
Springer
14 years 3 months ago
A Novel Tracking Framework Using Kalman Filtering and Elastic Matching
A novel region-based multiple object tracking framework based on Kalman filtering and elastic matching is proposed. The proposed Kalman filtering-elastic matching model is genera...
Xingzhi Luo, Suchendra M. Bhandarkar