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Oliver Schulte
Professor | Director, School of Computing Science
Computing Science
Areas of interest
Research Interests:
Machine Learning
Statistical Learning for Relational Databases
Computational Game Theory
Computational Logic
Teaching Interests:
Database Systems
Artificial Intelligence
Computers and Society
Education
- Ph.D. Logic and Computation, Carnegie Mellon University, USA, 1997
- M.Sc. Logic and Computation, Carnegie Mellon University, USA, 1993
- B.Sc. Computing Science, University of Toronto, Canada, 1992
Courses
Fall 2024
Future courses may be subject to change.
Selected Recent Publications
- A tractable pseudo-likelihood function for Bayes Nets Applied to Relational Data. SIAM Conference on Data Mining, 2011.
- Structure Learning for Markov Logic Networks with Many Descriptive Attributes. Hassan Khosravi, Oliver Schulte, Tong Man, Xiaoyuan Xu, Bahareh Bina (2010). Proceedings of the Twenty-Fourth Conference on Artificial Intelligence (AAAI), pp.487-493.
- The Imap Hybrid Method for Learning Gaussian Bayes Nets. O. Schulte, G.Frigo, R. Greiner and H. Khosravi (2010). Proceedings of the 23rd Canadian Conference on Artificial Intelligence (CANAI), pp.123--134, Springer LNCS 6085. Best Paper Award.
- Simultaneous Discovery of Conservation Laws and Hidden Particles With Smith Matrix Decomposition . Schulte, O. (2009). Proceedings of the Twenty-First International Joint Conference on Artificial Intelligence (IJCAI-09), pp. 1481-1487.
- Mind-change optimal learning of Bayes net structure from dependency and independency data. Schulte, O., W. Luo, and R. Greiner (2010). Information and Computation, 208:63-82.
For more information visit www.cs.sfu.ca/~oschulte/pubs.html.
Listing on the DBLP CS Bibliography Server.