We propose a logical/mathematical framework for statistical parameter learning of parameterized logic programs, i.e. denite clause programs containing probabilistic facts with a ...
In this paper, we propose a post randomization technique to learn a Bayesian network (BN) from distributed heterogeneous data, in a privacy sensitive fashion. In this case, two or ...
This paper proposes the incremental Bayesian optimization algorithm (iBOA), which modifies standard BOA by removing the population of solutions and using incremental updates of t...
Text clustering is most commonly treated as a fully automated task without user supervision. However, we can improve clustering performance using supervision in the form of pairwi...
Understanding human emotions is one of the necessary skills for the computer to interact intelligently with human users. The most expressive way humans display emotions is through...
Ira Cohen, Nicu Sebe, Fabio Gagliardi Cozman, Marc...