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ESSMAC
2003
Springer
16 years 25 days ago
Self-tuning Control of Non-linear Systems Using Gaussian Process Prior Models
Gaussian Process prior models, as used in Bayesian non-parametric statistical models methodology are applied to implement a nonlinear adaptive control law. The expected value of a...
Daniel Sbarbaro, Roderick Murray-Smith
DASC
2006
IEEE
15 years 9 months ago
Autonomic Sensor Networks: A New Paradigm for Collaborative Information Processing
Wireless Sensor Networks (WSNs) are severely constrained in computation and communication capabilities due to the cost and size of available sensors. On the other hand, autonomic ...
Hui Kang, Xiaolin Li, Patrick J. Moran
ECAI
2008
Springer
15 years 9 months ago
A Simulation-based Approach for Solving Generalized Semi-Markov Decision Processes
Time is a crucial variable in planning and often requires special attention since it introduces a specific structure along with additional complexity, especially in the case of dec...
Emmanuel Rachelson, Gauthier Quesnel, Fréd&...
NIPS
2007
15 years 9 months ago
Inferring Neural Firing Rates from Spike Trains Using Gaussian Processes
Neural spike trains present challenges to analytical efforts due to their noisy, spiking nature. Many studies of neuroscientific and neural prosthetic importance rely on a smooth...
John P. Cunningham, Byron M. Yu, Krishna V. Shenoy...
NIPS
2003
15 years 9 months ago
Hierarchical Topic Models and the Nested Chinese Restaurant Process
We address the problem of learning topic hierarchies from data. The model selection problem in this domain is daunting—which of the large collection of possible trees to use? We...
David M. Blei, Thomas L. Griffiths, Michael I. Jor...