: We present the implementation of on-line Hebbian learning for NESPINN, the Neurocomputer for the simulation of spiking neurons. In order to support various forms of Hebbian learn...
Abstract. This paper presents a machine learning approach for paraphrase identification which uses lexical and semantic similarity information. In the experimental studies, we exam...
Automated text categorisation systems learn a generalised hypothesis from large numbers of labelled examples. However, in many domains labelled data is scarce and expensive to obta...
The Sensitivity-Based Linear Learning Method (SBLLM) is a learning method for two-layer feedforward neural networks, based on sensitivity analysis, that calculates the weights by s...
Learning by imitation has shown to be a powerful paradigm for automated learning in autonomous robots. This paper presents a general framework of learning by imitation for stochas...