Complex tasks like question answering need to be able to identify events in text and the relations among those events. We show that this event identification task and a related ta...
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...
We propose a modular reinforcement learning architecture for non-linear, nonstationary control tasks, which we call multiple model-based reinforcement learning (MMRL). The basic i...
In this paper, we present a two-dimensional approach of the processing of handwriting. It combines a Markovian model, an efficient decoding algorithm, a windowed spectral feature...
A fuzzy inference model for learning from experiences (FILE) is proposed. The model can learn from experience data obtained by trial-and-error of a task and it can stably learn fr...