Abstract. Both symbolic knowledge representation systems and artificial neural networks play a significant role in Artificial Intelligence. A recent trend in the field aims at ...
Ilianna Kollia, Nikos Simou, Giorgos B. Stamou, An...
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...
We propose a neuro-genetic daily stock prediction model. Traditional indicators of stock prediction are utilized to produce useful input features of neural networks. The genetic al...
Recurrent neural networks fail to deal with prediction tasks which do not satisfy the causality assumption. We propose to exploit bi-causality to extend the Recurrent Cascade Corr...
Cognitive modeling with neural networks unrealistically ignores the role of knowledge in learning by starting from random weights. It is likely that effective use of knowledge by ...