*Who:* Scanagatta Mauro, Ph.D. Candidate @ IDSIA
*Title:* Advancements in Bayesian network structure learning
***Abstract: *A Bayesian network (BN) is a versatile and well-known probabilistic
graphical model with applications in a variety of fields.
Their graphical nature makes BNs excellent models for representing the complex
probabilistic relationships existing in many real problems ranging from bioinformatics to
law, from image processing to economic risk analysis.
In this talk, we will present the difficult task of learning their dependency graph, also
known as their structure, from data.
***When:* Wednesday, 28th of March 2018, 12:00-13:00
*Where: *Manno, Galleria 1, 2nd floor, room G1-204
*Registration: *Pizza kebab (or alternative food) and drinks will be offered at the end of
If you plan to attend, please register in a timely fashion at the following link so that
we will have no shortage of food:
Ph.D. Student @ IDSIA -
Institute Dalle Molle for Artificial Intelligence