This paper's intention is to adapt prediction algorithms well known in the field of time series analysis to problems being faced in the field of mobile robotics and Human-Robo...
Representing lexicons and sentences with the subsymbolic approach (using techniques such as Self Organizing Map (SOM) or Artificial Neural Network (ANN)) is a relatively new but i...
We propose a new approach for learning Bayesian classifiers from data. Although it relies on traditional Bayesian network (BN) learning algorithms, the effectiveness of our approa...
We present a time–parallel technique for the fast generation of self–similar traffic which is suitable for performance studies of Asynchronous Transfer Mode (ATM) networks. Th...
Ioanis Nikolaidis, C. Anthony Cooper, Kalyan S. Pe...
We consider learning tasks where multiple target variables need to be predicted. Two approaches have been used in this setting: (a) build a separate single-target model for each ta...