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» Approximations of Bayesian Networks through KL Minimisation
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76
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NGC
2000
Springer
105views Communications» more  NGC 2000»
15 years 1 months ago
Approximations of Bayesian Networks through KL Minimisation
Wim Wiegerinck, Bert Kappen
ICML
2005
IEEE
16 years 2 months ago
Healing the relevance vector machine through augmentation
The Relevance Vector Machine (RVM) is a sparse approximate Bayesian kernel method. It provides full predictive distributions for test cases. However, the predictive uncertainties ...
Carl Edward Rasmussen, Joaquin Quiñonero Ca...
ICCV
2001
IEEE
16 years 3 months ago
Continuous Global Evidence-Based Bayesian Modality Fusion for Simultaneous Tracking of Multiple Objects
Robust, real-time tracking of objects from visual data requires probabilistic fusion of multiple visual cues. Previous approaches have either been ad hoc or relied on a Bayesian n...
Jamie Sherrah, Shaogang Gong
CMSB
2009
Springer
15 years 8 months ago
Probabilistic Approximations of Signaling Pathway Dynamics
Systems of ordinary differential equations (ODEs) are often used to model the dynamics of complex biological pathways. We construct a discrete state model as a probabilistic appro...
Bing Liu, P. S. Thiagarajan, David Hsu
131
Voted
CDC
2009
IEEE
208views Control Systems» more  CDC 2009»
15 years 3 months ago
Sensor selection for hypothesis testing in wireless sensor networks: a Kullback-Leibler based approach
We consider the problem of selecting a subset of p out of n sensors for the purpose of event detection, in a wireless sensor network (WSN). Occurrence or not of the event of intere...
Dragana Bajovic, Bruno Sinopoli, João Xavie...