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ICML
2008
IEEE
14 years 9 months ago
Gaussian process product models for nonparametric nonstationarity
Stationarity is often an unrealistic prior assumption for Gaussian process regression. One solution is to predefine an explicit nonstationary covariance function, but such covaria...
Ryan Prescott Adams, Oliver Stegle
ICML
2005
IEEE
14 years 9 months ago
Reinforcement learning with Gaussian processes
Gaussian Process Temporal Difference (GPTD) learning offers a Bayesian solution to the policy evaluation problem of reinforcement learning. In this paper we extend the GPTD framew...
Yaakov Engel, Shie Mannor, Ron Meir
CVPR
2010
IEEE
1790views Computer Vision» more  CVPR 2010»
14 years 5 months ago
Data Driven Mean-Shift Belief Propagation For non-Gaussian MRFs
We introduce a novel data-driven mean-shift belief propagation (DDMSBP) method for non-Gaussian MRFs, which often arise in computer vision applications. With the aid of scale sp...
Minwoo Park, S. Kashyap, R. Collins, and Y. Liu
ICASSP
2008
IEEE
14 years 3 months ago
Performance characteristics of collaborative beamforming for wireless sensor networks with Gaussian distributed sensor nodes
Collaborative beamforming has been recently introduced in the context of wireless sensor networks (WSNs) to increase the transmission range of individual sensor nodes. In this pap...
Mohammed F. A. Ahmed, Sergiy A. Vorobyov
ICPR
2008
IEEE
14 years 3 months ago
Combining shape-from-shading and stereo using Gaussian-Markov random fields
In this paper we present a method of combining stereo and shape-from-shading information, taking account of the local reliability of each shape estimate. Local estimates of dispar...
Tom S. F. Haines, Richard C. Wilson