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NPL
2006
85views more  NPL 2006»
13 years 7 months ago
A Neural Model for Context-dependent Sequence Learning
A novel neural network model is described that implements context-dependent learning of complex sequences. The model utilises leaky integrate-and-fire neurons to extract timing inf...
Luc Berthouze, Adriaan G. Tijsseling
AGI
2008
13 years 9 months ago
Probabilistic Quantifier Logic for General Intelligence: An Indefinite Probabilities Approach
: Indefinite probabilities are a novel technique for quantifying uncertainty, which were created as part of the PLN (Probabilistic Logic Networks) logical inference engine, which i...
Matthew Iklé, Ben Goertzel
ESANN
2006
13 years 9 months ago
Neural networks and machine learning in bioinformatics - theory and applications
Bioinformatics is a promising and innovative research field. Despite of a high number of techniques specifically dedicated to bioinformatics problems as well as many successful app...
Udo Seiffert, Barbara Hammer, Samuel Kaski, Thomas...
ICML
2010
IEEE
13 years 8 months ago
Mixed Membership Matrix Factorization
Discrete mixed membership modeling and continuous latent factor modeling (also known as matrix factorization) are two popular, complementary approaches to dyadic data analysis. In...
Lester W. Mackey, David Weiss, Michael I. Jordan
ISER
1999
Springer
114views Robotics» more  ISER 1999»
13 years 12 months ago
Continuous Probabilistic Mapping by Autonomous Robots
In this paper, we present a new approach for continuous probabilistic mapping. The objective is to build metric maps of unknown environments through cooperation between multiple au...
Jesús Salido Tercero, Christiaan J. J. Pare...