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ICANN
2010
Springer
15 years 3 months ago
Dynamic Shape Learning and Forgetting
In this paper, we present a system capable of dynamically learning shapes in a way that also allows for the dynamic deletion of shapes already learned. It uses a self-balancing Bin...
Nikolaos Tsapanos, Anastasios Tefas, Ioannis Pitas
IJAR
2010
152views more  IJAR 2010»
15 years 3 months ago
Structural-EM for learning PDG models from incomplete data
Probabilistic Decision Graphs (PDGs) are a class of graphical models that can naturally encode some context specific independencies that cannot always be efficiently captured by...
Jens D. Nielsen, Rafael Rumí, Antonio Salme...
IPSN
2010
Springer
15 years 1 months ago
i-MAC - a MAC that learns
Traffic patterns in manufacturing machines exhibit strong temporal correlations due to the underlying repetitive nature of their operations. A MAC protocol can potentially learn t...
Krishna Kant Chintalapudi
ICANN
2011
Springer
14 years 8 months ago
Learning from Multiple Annotators with Gaussian Processes
Abstract. In many supervised learning tasks it can be costly or infeasible to obtain objective, reliable labels. We may, however, be able to obtain a large number of subjective, po...
Perry Groot, Adriana Birlutiu, Tom Heskes
VISUALIZATION
2005
IEEE
15 years 10 months ago
Opening the Black Box - Data Driven Visualization of Neural Network
Arti cial neural networks are computer software or hardware models inspired by the structure and behavior of neurons in the human nervous system. As a powerful learning tool, incr...
Fan-Yin Tzeng, Kwan-Liu Ma