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ESANN
2003
15 years 1 months ago
Autonomous learning algorithm for fully connected recurrent networks
In this paper fully connected RTRL neural networks are studied. In order to learn dynamical behaviours of linear-processes or to predict time series, an autonomous learning algori...
Edouard Leclercq, Fabrice Druaux, Dimitri Lefebvre
ETS
2002
IEEE
142views Hardware» more  ETS 2002»
14 years 11 months ago
A Framework for Technology Convergence in Learning and Working
Information technology is arguably an important tool for knowledge management, facilitating learning in a business context. However, the current use of information technology in t...
Miltiadis D. Lytras, Athanasia Pouloudi, Angeliki ...
ICMLA
2010
14 years 9 months ago
Incremental Learning of Relational Action Rules
Abstract--In the Relational Reinforcement learning framework, we propose an algorithm that learns an action model allowing to predict the resulting state of each action in any give...
Christophe Rodrigues, Pierre Gérard, C&eacu...
ICGI
1998
Springer
15 years 4 months ago
Learning Stochastic Finite Automata from Experts
We present in this paper a new learning problem called learning distributions from experts. In the case we study the experts are stochastic deterministic finite automata (sdfa). W...
Colin de la Higuera
DAGM
2008
Springer
15 years 1 months ago
Learning Visual Compound Models from Parallel Image-Text Datasets
Abstract. In this paper, we propose a new approach to learn structured visual compound models from shape-based feature descriptions. We use captioned text in order to drive the pro...
Jan Moringen, Sven Wachsmuth, Sven J. Dickinson, S...