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» The limitation of Bayesianism
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TSP
2010
13 years 1 months ago
Robust precoding with Bayesian error modeling for limited feedback MU-MISO systems
We consider the robust precoder design for Multi-User Multiple Input Single Output (MU-MISO) systems where the Channel State Information (CSI) is fed back from the single antenna ...
Michael Joham, Paula Maria Castro, Luis Castedo, W...
ICANN
2009
Springer
13 years 10 months ago
Efficient Uncertainty Propagation for Reinforcement Learning with Limited Data
In a typical reinforcement learning (RL) setting details of the environment are not given explicitly but have to be estimated from observations. Most RL approaches only optimize th...
Alexander Hans, Steffen Udluft
JMLR
2002
74views more  JMLR 2002»
13 years 6 months ago
The Representational Power of Discrete Bayesian Networks
One of the most important fundamental properties of Bayesian networks is the representational power, reflecting what kind of functions they can or cannot represent. In this paper,...
Charles X. Ling, Huajie Zhang
ICASSP
2010
IEEE
13 years 7 months ago
Fundamental limits of image denoising: Are we there yet?
In this paper, we study the fundamental performance limits of image denoising where the aim is to recover the original image from its noisy observation. Our study is based on a ge...
Priyam Chatterjee, Peyman Milanfar
IPSN
2004
Springer
14 years 9 days ago
A probabilistic approach to inference with limited information in sensor networks
We present a methodology for a sensor network to answer queries with limited and stochastic information using probabilistic techniques. This capability is useful in that it allows...
Rahul Biswas, Sebastian Thrun, Leonidas J. Guibas