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NIPS
2004
13 years 8 months ago
Dynamic Bayesian Networks for Brain-Computer Interfaces
We describe an approach to building brain-computer interfaces (BCI) based on graphical models for probabilistic inference and learning. We show how a dynamic Bayesian network (DBN...
Pradeep Shenoy, Rajesh P. N. Rao
AUSAI
2006
Springer
13 years 10 months ago
Robust Character Recognition Using a Hierarchical Bayesian Network
There is increasing evidence to suggest that the neocortex of the mammalian brain does not consist of a collection of specialised and dedicated cortical architectures, but instead ...
John Thornton, Torbjorn Gustafsson, Michael Blumen...
AAAI
2012
11 years 9 months ago
An Object-Based Bayesian Framework for Top-Down Visual Attention
We introduce a new task-independent framework to model top-down overt visual attention based on graphical models for probabilistic inference and reasoning. We describe a Dynamic B...
Ali Borji, Dicky N. Sihite, Laurent Itti
WOWMOM
1998
ACM
106views Multimedia» more  WOWMOM 1998»
13 years 11 months ago
A Systems Approach to Prediction, Compensation and Adaptation in Wireless Networks
This paper presents a framework for provisioning application and channel dependent quality of service in wireless networks. The framework is based on three di erent adaptation mec...
Javier Gomez, Andrew T. Campbell, Hiroyuki Morikaw...
ICML
2008
IEEE
14 years 7 months ago
Laplace maximum margin Markov networks
We propose Laplace max-margin Markov networks (LapM3 N), and a general class of Bayesian M3 N (BM3 N) of which the LapM3 N is a special case with sparse structural bias, for robus...
Jun Zhu, Eric P. Xing, Bo Zhang