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» Kolmogorov-Loveland Randomness and Stochasticity
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NIPS
1996
15 years 3 months ago
Continuous Sigmoidal Belief Networks Trained using Slice Sampling
Real-valued random hidden variables can be useful for modelling latent structure that explains correlations among observed variables. I propose a simple unit that adds zero-mean G...
Brendan J. Frey
ICIP
2003
IEEE
16 years 3 months ago
Algorithms for stochastic approximations of curvature flows
Curvature flows have been extensively considered from a deterministic point of view. They have been shown to be useful for a number of applications including crystal growth, flame...
Gozde B. Unal, Delphine Nain, G. Ben-Arous, Nahum ...
GRID
2004
Springer
15 years 7 months ago
A Stochastic Control Model for Deployment of Dynamic Grid Services
We introduce a formal model for deployment and hosting of a dynamic grid service wherein the service provider must pay a resource provider for the use of computational resources. ...
Darin England, Jon B. Weissman
NIPS
2001
15 years 3 months ago
Stochastic Mixed-Signal VLSI Architecture for High-Dimensional Kernel Machines
A mixed-signal paradigm is presented for high-resolution parallel innerproduct computation in very high dimensions, suitable for efficient implementation of kernels in image proce...
Roman Genov, Gert Cauwenberghs
VISAPP
2007
15 years 3 months ago
Image deconvolution using a stochastic differential equation approach
We consider the problem of image deconvolution. We foccus on a Bayesian approach which consists of maximizing an energy obtained by a Markov Random Field modeling. MRFs are classi...
Xavier Descombes, M. Lebellego, Elena Zhizhina