Online Text Prediction with Recurrent Neural Networks
Neural Processing Letters
Online Symbolic-Sequence Prediction with Discrete-Time Recurrent Neural Networks
ICANN '01 Proceedings of the International Conference on Artificial Neural Networks
A neural probabilistic language model
The Journal of Machine Learning Research
Continuous space language models
Computer Speech and Language
Image compression based on the neural network art
Cybernetics and Systems Analysis
Anticipatory Behavior in Adaptive Learning Systems
DS'07 Proceedings of the 10th international conference on Discovery science
Scientific data lossless compression using fast neural network
ISNN'06 Proceedings of the Third international conference on Advances in Neural Networks - Volume Part I
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The purpose of this paper is to show that neural networks may be promising tools for data compression without loss of information. We combine predictive neural nets and statistical coding techniques to compress text files. We apply our methods to certain short newspaper articles and obtain compression ratios exceeding those of the widely used Lempel-Ziv algorithms (which build the basis of the UNIX functions “compress” and “gzip”). The main disadvantage of our methods is that they are about three orders of magnitude slower than standard methods