Abstract— This paper reports on our efforts to link an industrial state-of-the-art modelling tool to academic state-of-the-art analysis algorithms. In a nutshell, we enable timed...
Obtaining performance models, like Markov chains and queueing networks, for systems of significant complexity and magnitude is a difficult task that is usually tackled using human...
We propose in this paper a novel approach to the induction of the structure of Hidden Markov Models. The induced model is seen as a lumped process of a Markov chain. It is construc...
Abstract. One of the main problems when creating execution-level process models is finding implementations for process activities. Carrying out this activity manually can be time ...
Generative kernels represent theoretically grounded tools able to increase the capabilities of generative classification through a discriminative setting. Fisher Kernel is the fi...
Manuele Bicego, Marco Cristani, Vittorio Murino, E...