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AROBOTS
2004
99views more  AROBOTS 2004»
14 years 10 months ago
Bayesian Robot Programming
We propose a new method to program robots based on Bayesian inference and learning. It is called BRP for Bayesian Robot Programming. The capacities of this programming method are d...
Olivier Lebeltel, Pierre Bessière, Julien D...
FLAIRS
2009
14 years 8 months ago
Multiagent Bayesian Forecasting of Time Series with Graphical Models
Time series are found widely in engineering and science. We study multiagent forecasting in time series, drawing from literature on time series, graphical models, and multiagent s...
Yang Xiang, James Smith, Jeff Kroes
JMLR
2010
152views more  JMLR 2010»
14 years 5 months ago
Bayesian Generalized Kernel Models
We propose a fully Bayesian approach for generalized kernel models (GKMs), which are extensions of generalized linear models in the feature space induced by a reproducing kernel. ...
Zhihua Zhang, Guang Dai, Donghui Wang, Michael I. ...
ICML
2008
IEEE
15 years 11 months ago
Multi-task compressive sensing with Dirichlet process priors
Compressive sensing (CS) is an emerging field that, under appropriate conditions, can significantly reduce the number of measurements required for a given signal. In many applicat...
Yuting Qi, Dehong Liu, David B. Dunson, Lawrence C...
EVENT
2001
140views more  EVENT 2001»
15 years 10 days ago
Multimodal 3-D Tracking and Event Detection via the Particle Filter
Determining the occurrence of an event is fundamental to developing systems that can observe and react to them. Often, this determination is based on collecting video and/or audio...
Dmitry N. Zotkin, Ramani Duraiswami, Larry S. Davi...