Frequently, sequences of state transitions are triggered by specific signals. Learning these triggered sequences with recurrent neural networks implies storing them as different at...
In regression problems, making accurate predictions is often the primary goal. Also, relevance of inputs in the prediction of an output would be valuable information in many cases....
In this paper we propose an extension of sequence kernels to the case where the symbols that define the sequences have multiple representations. This configuration occurs in natura...
Abstract. This paper discusses a machine learning approach for binary classification problems which satisfies the specific requirements of safety-related applications. The approach...
Abstract. An architecture for achieving word recognition and incremental learning of new words in a language processing system is presented. The architecture is based on neural ass...