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NIPS
2008
15 years 8 months ago
Non-stationary dynamic Bayesian networks
Abstract: Structure learning of dynamic Bayesian networks provide a principled mechanism for identifying conditional dependencies in time-series data. This learning procedure assum...
Joshua W. Robinson, Alexander J. Hartemink
NIPS
2007
15 years 8 months ago
Congruence between model and human attention reveals unique signatures of critical visual events
Current computational models of bottom-up and top-down components of attention are predictive of eye movements across a range of stimuli and of simple, fixed visual tasks (such a...
Robert J. Peters, Laurent Itti
NIPS
2007
15 years 8 months ago
Locality and low-dimensions in the prediction of natural experience from fMRI
Functional Magnetic Resonance Imaging (fMRI) provides dynamical access into the complex functioning of the human brain, detailing the hemodynamic activity of thousands of voxels d...
Francois Meyer, Greg Stephens
NIPS
2007
15 years 8 months ago
The Price of Bandit Information for Online Optimization
In the online linear optimization problem, a learner must choose, in each round, a decision from a set D ⊂ Rn in order to minimize an (unknown and changing) linear cost function...
Varsha Dani, Thomas P. Hayes, Sham Kakade
NIPS
2007
15 years 8 months ago
A neural network implementing optimal state estimation based on dynamic spike train decoding
It is becoming increasingly evident that organisms acting in uncertain dynamical environments often employ exact or approximate Bayesian statistical calculations in order to conti...
Omer Bobrowski, Ron Meir, Shy Shoham, Yonina C. El...
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