It is often possible to combine observed data with background knowledge, perhaps expressed as a set of rules or as a terminology. There has been significant work on the combination of data-centered methods, often based on probabilities, and knowledge-based cues, often based on logical languages. In this talk, we will examine a number of tools that can help one combine data and knowledge when trying to learn a model.
Fabio G. Cozman is Full Professor at Escola Politecnica, Universidade de São Paulo, where he is the head of the Mechatronics Department. After finishing his PhD at Carnegie Mellon University (USA), Fabio has worked on automating decision-making and on machine learning techniques.