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NIPS
2003
13 years 9 months ago
Minimising Contrastive Divergence in Noisy, Mixed-mode VLSI Neurons
This paper presents VLSI circuits with continuous-valued probabilistic behaviour realized by injecting noise into each computing unit(neuron). Interconnecting the noisy neurons fo...
Hsin Chen, Patrice Fleury, Alan F. Murray
GECCO
2009
Springer
107views Optimization» more  GECCO 2009»
14 years 1 months ago
A stigmergy-based algorithm for black-box optimization: noisy function testbed
In this paper, we present a stigmergy-based algorithm for solving optimization problems with continuous variables, labeled Differential Ant-Stigmergy Algorithm (DASA). The perfor...
Peter Korosec, Jurij Silc
GECCO
2009
Springer
162views Optimization» more  GECCO 2009»
13 years 6 months ago
Uncertainty handling CMA-ES for reinforcement learning
The covariance matrix adaptation evolution strategy (CMAES) has proven to be a powerful method for reinforcement learning (RL). Recently, the CMA-ES has been augmented with an ada...
Verena Heidrich-Meisner, Christian Igel
IPSN
2005
Springer
14 years 1 months ago
Adaptive statistical sampling methods for decentralized estimation and detection of localized phenomena
— Sensor networks (SNETs) for monitoring spatial phenomena has emerged as an area of significant practical interest. We focus on the important problem of detection of distribute...
Erhan Baki Ermis, Venkatesh Saligrama
JMIV
2007
114views more  JMIV 2007»
13 years 8 months ago
Noisy Image Decomposition: A New Structure, Texture and Noise Model Based on Local Adaptivity
These last few years, image decomposition algorithms have been proposed to split an image into two parts: the structures and the textures. These algorithms are not adapted to the ...
Jérôme Gilles