Sciweavers

ESANN
2006
13 years 5 months ago
Evolino for recurrent support vector machines
Abstract. We introduce a new class of recurrent, truly sequential SVM-like devices with internal adaptive states, trained by a novel method called EVOlution of systems with KErnel-...
Jürgen Schmidhuber, Matteo Gagliolo, Daan Wie...
FLAIRS
2004
13 years 5 months ago
Recurrent Neural Networks and Pitch Representations for Music Tasks
We present results from experiments in using several pitch representations for jazz-oriented musical tasks performed by a recurrent neural network. We have run experiments with se...
Judy A. Franklin
NIPS
2008
13 years 5 months ago
Offline Handwriting Recognition with Multidimensional Recurrent Neural Networks
Offline handwriting recognition--the transcription of images of handwritten text--is an interesting task, in that it combines computer vision with sequence learning. In most syste...
Alex Graves, Jürgen Schmidhuber
ICONIP
2007
13 years 5 months ago
RNN with a Recurrent Output Layer for Learning of Naturalness
– The behavior of recurrent neural networks with a recurrent output layer (ROL) is described mathematically and it is shown that using ROL is not only advantageous, but is in fac...
Ján Dolinský, Hideyuki Takagi
ICONIP
2007
13 years 5 months ago
Practical Recurrent Learning (PRL) in the Discrete Time Domain
One of the authors has proposed a simple learning algorithm for recurrent neural networks, which requires computational cost and memory capacity in practical order O(n2 )[1]. The a...
Mohamad Faizal Bin Samsudin, Takeshi Hirose, Katsu...
ESANN
2008
13 years 5 months ago
Pruning and Regularisation in Reservoir Computing: a First Insight
Reservoir Computing is a new paradigm for using Recurrent Neural Networks which shows promising results. However, as the recurrent part is created randomly, it typically needs to b...
Xavier Dutoit, Benjamin Schrauwen, Jan M. Van Camp...
ESANN
2007
13 years 5 months ago
An overview of reservoir computing: theory, applications and implementations
Training recurrent neural networks is hard. Recently it has however been discovered that it is possible to just construct a random recurrent topology, and only train a single linea...
Benjamin Schrauwen, David Verstraeten, Jan M. Van ...
ACSC
2008
IEEE
13 years 6 months ago
An investigation of the state formation and transition limitations for prediction problems in recurrent neural networks
Recurrent neural networks are able to store information about previous as well as current inputs. This "memory" allows them to solve temporal problems such as language r...
Angel Kennedy, Cara MacNish
EVOW
2006
Springer
13 years 8 months ago
Continuous-Time Recurrent Neural Networks for Generative and Interactive Musical Performance
This paper describes an ongoing exploration into the use of Continuous-Time Recurrent Neural Networks (CTRNNs) as generative and interactive performance tools, and using Genetic Al...
Oliver Bown, Sebastian Lexer
ATAL
2006
Springer
13 years 8 months ago
Learning a common language through an emergent interaction topology
We study the effects of various emergent topologies of interaction on the rate of language convergence in a population of communicating agents. The agents generate, parse, and lea...
Samarth Swarup, Kiran Lakkaraju, Les Gasser