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» Generalizing Parametricity Using Information-flow
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CEC
2009
IEEE
14 years 1 months ago
Memory-enhanced Evolutionary Robotics: The Echo State Network Approach
— Interested in Evolutionary Robotics, this paper focuses on the acquisition and exploitation of memory skills. The targeted task is a well-studied benchmark problem, the Tolman ...
Cédric Hartland, Nicolas Bredeche, Mich&egr...
VISUALIZATION
2000
IEEE
14 years 1 months ago
Polyhedral modeling
Polyhedral meshes are used for visualization, computer graphics or geometric modeling purposes and result from many applications like iso-surface extraction, surface reconstructio...
Georges-Pierre Bonneau, Stefanie Hahmann
ICIAP
1999
ACM
14 years 1 months ago
Self-Training Statistic Snake for Image Segmentation and Tracking
In this work we propose a new supervised deformable model that generalizes the classical contour-based snake. This model is defined to deform in a feature space generated by a se...
Xose Manuel Pardo, Petia Radeva, Juan José ...
UAI
2001
13 years 10 months ago
Iterative Markov Chain Monte Carlo Computation of Reference Priors and Minimax Risk
We present an iterative Markov chain Monte Carlo algorithm for computing reference priors and minimax risk for general parametric families. Our approach uses MCMC techniques based...
John D. Lafferty, Larry A. Wasserman
ICASSP
2010
IEEE
13 years 9 months ago
Statistical Resolution Limit for multiple parameters of interest and for multiple signals
The concept of Statistical Resolution Limit (SRL), which is defined as the minimal separation to resolve two closely spaced signals, is an important tool to quantify performance ...
Mohammed Nabil El Korso, Rémy Boyer, Alexan...