Chris Mesterharm's Home Page

Department of Computer Science Rutgers University Room: 15 CBIM mesterha@cs.rutgers.edu

I am a research scientist in the Rutgers Computer Science Department.

Research

My research interests include natural language processing, text based machine learning, and on-line learning algorithms. Here is a link to a short description of my research.

Publications

• Active Learning using On-line Algorithms. Chris Mesterharm and Michael J. Pazzani. KDD 2011, pages 850-858.
• Combinatorial Fusion with On-line Learning Algorithms. Chris Mesterharm and D. Frank Hsu. Fusion 2008, pages 850-858.
• Improving On-line Learning. Chris Mesterharm. Ph.D. dissertation. Department of Computer Science, Rutgers University, New Brunswick, NJ 2007.
• Experience-Efficient Learning in Associative Bandit Problems. Alexander Strehl, Chris Mesterharm, Michael Littman, and Haym Hirsh. ICML-2006, pages 889-896, 2006.
• On-line Learning with Delayed Label Feedback. Chris Mesterharm. ALT 2005, pages 399-123.
• Tracking Linear-threshold Concepts with Winnow. Chris Mesterharm. Journal of Machine Learning Research, pages 819-838, 2003.
• Using Linear-threshold Algorithms to Combine Multi-class Sub-experts. Chris Mesterharm. ICML 2003, pages 544-551, 2003.
• Tracking Linear-threshold Concepts with Winnow. Chris Mesterharm. COLT-2002, pages 138-152, 2002.
• Transforming Linear-threshold Learning Algorithms into Multi-class Linear Learning Algorithms. Chris Mesterharm. Rutgers technical report, dcs-tr-460, 2001.
• A Multi-class Linear Learning Algorithm Related to Winnow. Chris Mesterharm. NIPS-12, pages 519-525, 2000.
• An Apobayesian Relative of Winnow. Nick Littlestone and Chris Mesterharm. NIPS 9, pages 204-210, 1997.

Resume

• Here is a link to my resume.

Teaching

• Here is a link to some slides I created on statistical learning theory.