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» Neural Dynamics with Stochasticity
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JMLR
2010
157views more  JMLR 2010»
14 years 7 months ago
Why are DBNs sparse?
Real stochastic processes operating in continuous time can be modeled by sets of stochastic differential equations. On the other hand, several popular model families, including hi...
Shaunak Chatterjee, Stuart Russell
127
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WIOPT
2011
IEEE
14 years 4 months ago
LIFO-Backpressure achieves near optimal utility-delay tradeoff
There has been considerable recent work developing a new stochastic network utility maximization framework using Backpressure algorithms, also known as MaxWeight. A key open probl...
Longbo Huang, Scott Moeller, Michael J. Neely, Bha...
122
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ICANN
2005
Springer
15 years 6 months ago
Image Segmentation by Complex-Valued Units
Spike synchronisation and de-synchronisation are important for feature binding and separation at various levels in the visual system. We present a model of complex valued neuron ac...
Cornelius Weber, Stefan Wermter
ESANN
2008
15 years 2 months ago
A Method for Time Series Prediction using a Combination of Linear Models
This paper presents a new approach for time series prediction using local dynamic modeling. The proposed method is composed of three blocks: a Time Delay Line that transforms the o...
David Martínez-Rego, Oscar Fontenla-Romero,...
JMLR
2006
124views more  JMLR 2006»
15 years 20 days ago
Policy Gradient in Continuous Time
Policy search is a method for approximately solving an optimal control problem by performing a parametric optimization search in a given class of parameterized policies. In order ...
Rémi Munos