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CIMCA
2005
IEEE
16 years 1 months ago
Oscillatory neural network for adaptive dynamical image processing
We develop a biologically motivated oscillatory network model and related dynamical synchronizationbased method of image segmentation. The first version of successive segmentation...
Margarita Kuzmina, Edward A. Manykin
191
Voted
ESSMAC
2003
Springer
16 years 19 days ago
Filtered Gaussian Processes for Learning with Large Data-Sets
Kernel-based non-parametric models have been applied widely over recent years. However, the associated computational complexity imposes limitations on the applicability of those me...
Jian Qing Shi, Roderick Murray-Smith, D. M. Titter...
199
Voted
IPMU
2010
Springer
16 years 6 days ago
A New Adaptive Consensus Reaching Process Based on the Experts' Importance
Usually, in a group decision context, the importance level, confidence degree and amount of knowledge are very different among individuals. So, when all the individuals have to r...
Ignacio J. Pérez, Francisco Javier Cabreriz...
NIPS
2003
15 years 8 months ago
Gaussian Processes in Reinforcement Learning
We exploit some useful properties of Gaussian process (GP) regression models for reinforcement learning in continuous state spaces and discrete time. We demonstrate how the GP mod...
Carl Edward Rasmussen, Malte Kuss
199
Voted
WSC
2000
15 years 8 months ago
Simulation based design for a shipyard manufacturing process
Discrete event simulation can be used for virtual prototyping of new manufacturing facilities. Models built for this purpose must be easy to use, flexible, and provide a realistic...
Deborah J. Medeiros, Mark T. Traband, April Tribbl...