Abstract. Performance of real-time applications on network communication channels are strongly related to losses and temporal delays. Several studies showed that these network feat...
Pierluigi Salvo Rossi, Francesco Palmieri, Giulio ...
Abstract. Markov and Conditional random fields (CRFs) used in computer vision typically model only local interactions between variables, as this is computationally tractable. In t...
Bayesian networks are directed acyclic graphs that represent dependencies between variables in a probabilistic model. Many time series models, including the hidden Markov models (H...
For a social robot, the ability of learning tasks via human demonstration is very crucial. But most current approaches suffer from either the demanding of the huge amount of label...
Zhe Li, Sven Wachsmuth, Jannik Fritsch, Gerhard Sa...
In this paper the classical propositional assumption-based model is extended to incorporate probabilities for the assumptions. Then the whole model is placed into the framework of...