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ICANN
2005
Springer
13 years 10 months ago
Classifying Unprompted Speech by Retraining LSTM Nets
Abstract. We apply Long Short-Term Memory (LSTM) recurrent neural networks to a large corpus of unprompted speech- the German part of the VERBMOBIL corpus. Training first on a fra...
Nicole Beringer, Alex Graves, Florian Schiel, J&uu...
GECCO
2005
Springer
204views Optimization» more  GECCO 2005»
13 years 10 months ago
Modeling systems with internal state using evolino
Existing Recurrent Neural Networks (RNNs) are limited in their ability to model dynamical systems with nonlinearities and hidden internal states. Here we use our general framework...
Daan Wierstra, Faustino J. Gomez, Jürgen Schm...
GECCO
2005
Springer
155views Optimization» more  GECCO 2005»
13 years 10 months ago
Co-evolving recurrent neurons learn deep memory POMDPs
Recurrent neural networks are theoretically capable of learning complex temporal sequences, but training them through gradient-descent is too slow and unstable for practical use i...
Faustino J. Gomez, Jürgen Schmidhuber
CIMCA
2005
IEEE
13 years 10 months ago
An Accelerating Learning Algorithm for Block-Diagonal Recurrent Neural Networks
An efficient training method for block-diagonal recurrent neural networks is proposed. The method modifies the RPROP algorithm, originally developed for static models, in order to...
Paris A. Mastorocostas, Dimitris N. Varsamis, Cons...
IJCNN
2006
IEEE
13 years 10 months ago
Online Training of a Generalized Neuron with Particle Swarm Optimization
— Neural networks are used in a wide number of fields including signal and image processing, modeling and control and pattern recognition. Some of the most common type of neural ...
Raveesh Kiran, Sandhya R. Jetti, Ganesh K. Venayag...
IJCNN
2006
IEEE
13 years 10 months ago
Reservoir-based techniques for speech recognition
— A solution for the slow convergence of most learning rules for Recurrent Neural Networks (RNN) has been proposed under the terms Liquid State Machines (LSM) and Echo State Netw...
David Verstraeten, Benjamin Schrauwen, Dirk Stroob...
IJCNN
2006
IEEE
13 years 10 months ago
Learning using Dynamical Regime Identification and Synchronization
—This study proposes to generalize Hebbian learning by identifying and synchronizing the dynamical regimes of individual nodes in a recurrent network. The connection weights are ...
Nicolas Brodu
ICANN
2007
Springer
13 years 10 months ago
Multi-dimensional Recurrent Neural Networks
Abstract. Recurrent neural networks (RNNs) have proved effective at one dimensional sequence learning tasks, such as speech and online handwriting recognition. Some of the properti...
Alex Graves, Santiago Fernández, Jürge...
IJCNN
2007
IEEE
13 years 11 months ago
Toyota Prius HEV neurocontrol
A neural network controller for improved fuel efficiency of the Toyota Prius hybrid electric vehicle is proposed. A new method to detect and mitigate a battery fault is also pres...
Danil V. Prokhorov
ICANN
2009
Springer
13 years 11 months ago
Combining Multiple Inputs in HyperNEAT Mobile Agent Controller
In this paper we present neuro-evolution of neural network controllers for mobile agents in a simulated environment. The controller is obtained through evolution of hypercube encod...
Jan Drchal, Ondrej Kapral, Jan Koutník, Mir...