Page 1. A biologically motivated neural network architecture for the avoidance of catastrophic in... more Page 1. A biologically motivated neural network architecture for the avoidance of catastrophic interference JF Dale Addison, Garen Z Arevian, John MacIntyre University of Sunderland, School of Computing and Technology, St ...
Artificial Neural NetworksICANN 2007, Jan 1, 2007
Abstract. Recurrent Neural Network (RNN) models have been shown to perform well on artificial gra... more Abstract. Recurrent Neural Network (RNN) models have been shown to perform well on artificial grammars for sequential classification tasks over long-term time-dependencies. However, there is a distinct lack of the application of RNNs to real-world text classification tasks. This ...
Proceedings of the IEEE/WIC/ACM International …, Jan 1, 2007
This paper explores the application of recurrent neural networks for the task of robust text clas... more This paper explores the application of recurrent neural networks for the task of robust text classification of a real-world benchmarking corpus. There are many well-established approaches which are used for text classi-fication, but they fail to address the challenge from a more multi-...
Page 1. A biologically motivated neural network architecture for the avoidance of catastrophic in... more Page 1. A biologically motivated neural network architecture for the avoidance of catastrophic interference JF Dale Addison, Garen Z Arevian, John MacIntyre University of Sunderland, School of Computing and Technology, St ...
Artificial Neural NetworksICANN 2007, Jan 1, 2007
Abstract. Recurrent Neural Network (RNN) models have been shown to perform well on artificial gra... more Abstract. Recurrent Neural Network (RNN) models have been shown to perform well on artificial grammars for sequential classification tasks over long-term time-dependencies. However, there is a distinct lack of the application of RNNs to real-world text classification tasks. This ...
Proceedings of the IEEE/WIC/ACM International …, Jan 1, 2007
This paper explores the application of recurrent neural networks for the task of robust text clas... more This paper explores the application of recurrent neural networks for the task of robust text classification of a real-world benchmarking corpus. There are many well-established approaches which are used for text classi-fication, but they fail to address the challenge from a more multi-...
Uploads
Papers by Garen Arevian