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» Approximate Learning of Dynamic Models
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BC
2002
91views more  BC 2002»
15 years 6 months ago
Linear combinations of nonlinear models for predicting human-machine interface forces
ACT This study presents a computational framework that capitalizes on known human neuromechanical characteristics during limb movements in order to predict man-machine interactions...
James L. Patton, Ferdinando A. Mussa-Ivaldi
160
Voted
USENIX
2007
15 years 8 months ago
Reboots Are for Hardware: Challenges and Solutions to Updating an Operating System on the Fly
Patches to modern operating systems, including bug fixes and security updates, and the reboots and downtime they require, cause tremendous problems for system users and administr...
Andrew Baumann, Jonathan Appavoo, Robert W. Wisnie...
JCB
2006
185views more  JCB 2006»
15 years 6 months ago
Bayesian Sequential Inference for Stochastic Kinetic Biochemical Network Models
As postgenomic biology becomes more predictive, the ability to infer rate parameters of genetic and biochemical networks will become increasingly important. In this paper, we expl...
Andrew Golightly, Darren J. Wilkinson
ICASSP
2011
IEEE
14 years 10 months ago
Predictive modeling of the spatiotemporal evolution of an environmental hazard and its sensor network implementation
Predicting accurately the spatiotemporal evolution of a diffusive environmental hazard is of paramount importance for its effective containment. We approximate the front line of a...
Dimitris V. Manatakis, Elias S. Manolakos
PRL
2008
118views more  PRL 2008»
15 years 5 months ago
Bayes Machines for binary classification
In this work we propose an approach to binary classification based on an extension of Bayes Point Machines. Particularly, we take into account the whole set of hypotheses that are...
Daniel Hernández-Lobato, José Miguel...