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» Boosting in Probabilistic Neural Networks
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SSPR
1998
Springer
14 years 29 days ago
Modified Minimum Classification Error Learning and Its Application to Neural Networks
A novel method to improve the generalization performance of the Minimum Classification Error (MCE) / Generalized Probabilistic Descent (GPD) learning is proposed. The MCE/GPD learn...
Hiroshi Shimodaira, Jun Rokui, Mitsuru Nakai
AAAI
2006
13 years 10 months ago
When Gossip is Good: Distributed Probabilistic Inference for Detection of Slow Network Intrusions
Intrusion attempts due to self-propagating code are becoming an increasingly urgent problem, in part due to the homogeneous makeup of the internet. Recent advances in anomalybased...
Denver Dash, Branislav Kveton, John Mark Agosta, E...
ICANN
2009
Springer
14 years 1 months ago
Computing with Probabilistic Cellular Automata
Abstract. We investigate the computational capabilities of probabilistic cellular automata by means of the density classification problem. We find that a specific probabilistic ...
Martin Schüle, Thomas Ott, Ruedi Stoop
JIRS
2008
100views more  JIRS 2008»
13 years 8 months ago
Model-based Predictive Control of Hybrid Systems: A Probabilistic Neural-network Approach to Real-time Control
Abstract This paper proposes an approach for reducing the computational complexity of a model-predictive-control strategy for discrete-time hybrid systems with discrete inputs only...
Bostjan Potocnik, Gasper Music, Igor Skrjanc, Boru...
ICANN
2007
Springer
14 years 2 months ago
Probabilistic Video-Based Gesture Recognition Using Self-organizing Feature Maps
Present work introduces a probabilistic recognition scheme for hand gestures. Self organizing feature maps are used to model spatiotemporal information extracted through image proc...
George Caridakis, Christos Pateritsas, Athanasios ...