Anomaly detection for network intrusion detection is usually considered an unsupervised task. Prominent techniques, such as one-class support vector machines, learn a hypersphere ...
In this paper, learning algorithm for a single multiplicative spiking neuron (MSN) is proposed and tested for various applications where a multilayer perceptron (MLP) neural netwo...
In a typical reinforcement learning (RL) setting details of the environment are not given explicitly but have to be estimated from observations. Most RL approaches only optimize th...
This paper outlines a series of experiments looking at the annotation and subsequent analysis of skills-based learning and teaching in the domain of Nursing. The experiments used ...
Mark J. Weal, Danius T. Michaelides, Kevin R. Page...
Biological sensorimotor systems are not static maps that transform input sensory information into output motor behavior. Evidence from many lines of research suggests that their r...