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ESANN
2003
13 years 11 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
NIPS
1993
13 years 11 months ago
Credit Assignment through Time: Alternatives to Backpropagation
Learning to recognize or predict sequences using long-term context has many applications. However, practical and theoretical problems are found in training recurrent neural networ...
Yoshua Bengio, Paolo Frasconi
CIBCB
2005
IEEE
14 years 3 months ago
Artificial Neural Network Analysis of DNA Microarray-based Prostate Cancer Recurrence
— DNA microarray-based gene expression profiles have been established for a variety of adult cancers. This paper addresses application of an artificial neural network (ANN) wit...
Leif E. Peterson, Mustafa Ozen, Halime Erdem, Andr...
SOFSEM
2004
Springer
14 years 3 months ago
Approaches Based on Markovian Architectural Bias in Recurrent Neural Networks
Recent studies show that state-space dynamics of randomly initialized recurrent neural network (RNN) has interesting and potentially useful properties even without training. More p...
Matej Makula, Michal Cernanský, Lubica Benu...
ICRA
2009
IEEE
137views Robotics» more  ICRA 2009»
14 years 4 months ago
Continuous vocal imitation with self-organized vowel spaces in Recurrent Neural Network
Abstract— A continuous vocal imitation system was developed using a computational model that explains the process of phoneme acquisition by infants. Human infants perceive speech...
Hisashi Kanda, Tetsuya Ogata, Toru Takahashi, Kazu...