Jesse Davis

Post Doc

Address:
Dept. of Computer Science & Engineering
University of Washington
Box 352350
Seattle, WA 98195-2350

Telephone: (206) 543-4229
Fax: (206) 616-1798
Email: first initial + last name at cs dot washington dot edu
Office: 356 Allen Center

About Me

I am post-doc withPedro Domingos at the University of Washington. I work on Markov logic networks, which are publically available as the Alchemy system. I am also involved with our recent MURI award entitled A Unified Approach to Abductive Inference. I did my Ph.D at the University of Wisconsin-Madison. If you are interested you, can look at my old webpage

590A

In the spring of 2008, I ran a seminar on Biomedical Applications of Artificial Intelligence.

Education

Ph.D in Computer Sciences from the University of Wisconsin-Madison. (August 2007)

M.S. in Computer Sciences from the University of Wisconsin-Madison. (May 2005)

B.A. in Computer Science from Williams College. (June 2002)

Software

Mark Goadrich and I have written a java package for generating ROC and Precision Recall curves. It can also calculate the area under the curve. The jar file is available here. For more information about ROC and PR curves, see our paper at ICML 2006.

Publications

Refereed Conferences

Jesse Davis, Vitor Santos Costa, Soumya Ray and David Page (2007). An Integrated Approach to Feature Construction and Model Building for Drug Activity Prediction. In the Proceedings of the 24th International Conference on Machine Learning (ICML). Available as PDF.

Jesse Davis, Irene Ong, Jan Struyf, Elizabeth Burnside, David Page and Vitor Santos Costa (2007). Change of Representation for Statistical Relational Learning. In the Proceedings of the 20th International Joint Conference on Artificial Intelligence (IJCAI). Available as PDF.

Jesse Davis and Mark Goadrich (2006). The Relationship Between Precision-Recall and ROC Curves. In the Proceedings of the 23rd International Conference on Machine Learning (ICML). Available as PDF.

Jan Struyf, Jesse Davis and David Page (2006). An Efficient Approximation to Lookahead in Relational Learners. In the Proceedings of the 17th European Conference on Machine Learning (ECML). Available as PDF.

Jesse Davis, Elizabeth Burnside, Ines Dutra, David Page, Raghu Ramakrishnan, Vitor Santos Costa and Jude Shavlik (2005). View Learning for Statistical Relational Learning: With an Application to Mammography. In the Proceedings of the International Joint Conference on Artificial Intelligence (IJCAI). Available as postscript or PDF.

Jesse Davis, Ines Dutra, David Page and Vitor Santos Costa (2005). Establishing Identity Equivalence in Multi-Relational Domains. In the Proceedings of the International Conference on Intelligence Analysis. Available as postscript, PDF or Word. Winner of the Best Technical Paper award.

Elizabeth S. Burnside, Jesse Davis, Vitor Santos Costa, Ines Dutra, Charles E. Kahn Jr., Jason P. Fine and David Page (2005). Knowledge Discovery from Structured Mammography Reports Using Inductive Logic Programming. In the Proceeding of the American Medical Informatics Association Annual Symposium (AMIA) . Will be available shortly.

Jesse Davis, Elizabeth Burnside, Ines Dutra, David Page, Vitor Santos Costa (2005). An Integrated Approach to Learning Bayesian Networks of Rules. In the Proceedings of the European Conference of Machine Learning (ECML). Available as postscript or PDF.

Book Chapters

Jesse Davis, Elizabeth Burnside, Ines Dutra, David Page, Raghu Ramakrishnan, Vitor Santos Costa and Jude Shavlik (2007). Learning a New View of a Database: With an Application to Mammography. In L. Getoor and B. Taskar, editors, An Introduction to Statistical Relational Learning, MIT Press.

Refereed Workshops

Jesse Davis and Pedro Domingos (2008). Deep Transfer via Second-Order Markov Logic. To appear in the Proceedings of the AAAI-2008 Workshop on Transfer Learning for Complex Tasks. Chicago, IL: AAAI Press. Available as PDF

Jesse Davis, Elizabeth Burnside, David Page and Vitor Santos Costa (2006). View Learning Extended: Inventing New Tables for Statistical Relational Learning. In the Proceedings of Open Problems in Statistical Relational Learning Workshop (SRL2006). In conjunction with ICML 2006.

Jesse Davis, Vitor Santos Costa, Irene Ong, David Page and Ines Dutra (2004). Using Bayesian Classifiers to Combine Rules. Appears in the Proceedings of the 3rd Workshop on Multi-Relational Data Mining ( MRDM 2004). In conjunction with KDD 2004. Available as postscript or PDF.

Professional Service

Program Committee for the 2008 IEEE International Conference on Data Mining (ICDM-08)
Program Committee for the 23rd Conference on Artificial Intelligence (AAAI-08)
Program Committee for the 25th International Conference on Machine Learning (ICML-08)
Program Committe for the Track on Relational Learning (LEARN) at the 24th Annual ACM Symposium on Applied Computing
Program Committee for the 19th Brazilian Symposium on Artificial Intelligence (SBIA-08)
Reviewer for ACM Transactions on Knowledge Discovery from Data (2007)
Reviewer for Journal of Artificial Intelligence Research (2007)
Reviewer for Machine Learning Journal (2007)
Reviewer for 15th Annual International Conference on Intelligent Systems for Molecular Biology (ISMB-07)
Reviewer for the 20th International Joint Conference on Artificial Intelligence (IJCAI-07)
Reviewer for ACM Transactions on Computational Logic (2006)