MIDAS Seminar

Probabilistic Graphical Models and Online Learning

Tony Jebara, PhDAssociate Professor of Computer ScienceColumbia University

Jebara is Associate Editor for the Journal of Machine Learning Research and on the Editorial Board of Machine Learning. Jebara was Associate Editor of Machine Learning from 2007 to 2011 and Associate Editor of IEEE Transactions on Pattern Analysis and Machine Intelligence from 2010 to 2012. In 2006, he co-founded the NYAS Machine Learning Symposium and has served on its steering committee since then. Jebara will be a Program Chair for the 31st International Conference on Machine Learning (ICML) in 2014.
Tony Jebara is associate professor of Computer Science at Columbia University. He directs the Columbia Machine Learning Laboratory whose research intersects computer science and statistics to develop new frameworks for learning from data with applications in vision, networks, spatio-temporal data, and text. Jebara has founded and advised several startups including Sense Networks, Agolo, Ninoh and Bookt. He has published over 100 peer-reviewed papers in conferences, workshops and journals including NIPS, ICML, UAI, COLT, JMLR, CVPR, ICCV, and AISTAT. He is the author of the book Machine Learning: Discriminative and Generative and co-inventor on multiple patents in vision, learning and spatio-temporal modeling. In 2004, Jebara was the recipient of the Career award from the National Science Foundation. His work was recognized with a best paper award at the 26th International Conference on Machine Learning, a best student paper award at the 20th International Conference on Machine Learning as well as an outstanding contribution award from the Pattern Recognition Society in 2001. Jebara's research has been featured on television (ABC, BBC, New York One, TechTV, etc.) as well as in the popular press (New York Times, Slash Dot, Wired, Businessweek, IEEE Spectrum, etc.). He obtained his PhD in 2002 from MIT. Esquire magazine named him one of their Best and Brightest of 2008. Jebara has taught machine learning to well over 1000 students (through real physical classes).

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Faculty Host

Al Hero