WIC 2014 Tutorial - Directed Probabilistic Graphs: Learning and Inference

Directed Probabilistic Graphs: Learning and Inference

Marek J. Druzdzel School of Information Sciences, University of Pittsburgh, Pittsburgh, PA, USA, http://www.pitt.edu/~druzdzel
Department of Computer Science, Białystok University of Technology, Białystok, Poland, http://aragorn.wi.pb.bialystok.pl/~druzdzel/

SHORT DESCRIPTION: 
Directed probabilistic graphs, of which Bayesian networks are a prominent representative, are well known for their ability to tackle successfully hard practical problems.  Their success can be attributed to a unique combination of the intuitive framework of directed graphs and to the sound foundations of probability theory and decision theory on which they are built.  The tutorial will focus on the foundations of discrete directed probabilistic graphs, show how they can be built based on expert knowledge and applied to problems such as classification or diagnosis.  It will cover state of the art research on Bayesian networks and how they can be and have been extended to address a variety of problems.  It will show how Bayesian networks extend to continuous variables and temporal domains.  Finally, it will discuss fundamentals of learning directed probabilistic graphs and causal discovery from data, including causal discovery from time series. The tutorial will be fairly self-contained and intuitive for computer scientists, although familiarity with elementary probability theory will be helpful.

ABOUT THE TUTOR

Marek Druzdzel is an associate professor in the School of Information Sciences and in the Intelligent Systems Program and the director of the Decision Systems Laboratory (http://dsl.sis.pitt.edu/) at the University of Pittsburgh.  He is also a visiting professor in the Department of Computer Science, Bialystok University of Technology, Bialystok, Poland.  He received his M.S. degrees in Computer Science (1985) and Electrical Engineering (1987) from the Delft University of Technology in The Netherlands (both with distinction) and his Ph.D. in Engineering and Public Policy (1992) from Carnegie Mellon University, Pittsburgh, PA, USA.  Prof. Druzdzel is a recipient of the Faculty Early Career Development Grant (known as CAREER grant) from the National Science Foundation (1996-2000), Outstanding Mentor Award (1997), and University of Pittsburgh’s Chancellor’s Distinguished Teaching Award (2007).  He is also a recipient of the 2009-2010 Fulbright Award for teaching and research at the Bialystok University of Technology, Poland.  His research interests concentrate on probabilistic and decision theoretic methods in decision support systems and human aspect of decision support.  Decision Systems Laboratory that he created over 20 years ago is widely known for the graphical modeling software GeNIe, available at http://genie.sis.pitt.edu/ and used in many universities and corporations World-wide.  
More details about Prof. Druzdzel’s research interests along with a full list of publications are available at
http://www.pitt.edu/~druzdzel.

 

 

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