Supporting continuous mining queries on data streams requires algorithms that (i) are fast, (ii) make light demands on memory resources, and (iii) are easily to adapt to concept dr...
This paper describes a Conscious Tutoring System (CTS) capable of dynamic fine-tuned assistance to users. We put forth the combination of a Causal Learning and Emotional learning m...
Usef Faghihi, Philippe Fournier-Viger, Roger Nkamb...
—Mining temporal network models from discrete event streams is an important problem with applications in computational neuroscience, physical plant diagnostics, and human-compute...
In this paper we present the Dynamic Grow-Shrink Inference-based Markov network learning algorithm (abbreviated DGSIMN), which improves on GSIMN, the state-ofthe-art algorithm for...
Many applications involve a set of prediction tasks that must be accomplished sequentially through user interaction. If the tasks are interdependent, the order in which they are p...