Tony Jebara
homepage:http://www1.cs.columbia.edu/~jebara/
search externally:   Google Scholar,   Springer,   CiteSeer,   Microsoft Academic Search,   Scirus ,   DBlife

Description

Tony Jebara is Associate Professor of Computer Science at Columbia University and co-founder of Sense Networks. 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 published over 75 peer-reviewed papers in conferences 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 honorable mention from the Pattern Recognition Society in 2000. 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. Recently, Esquire magazine named him one of their Best and Brightest of 2008. Jebara's lab is supported in part by the NSF, CIA, NSA, DHS, and ONR.


Lectures:

invited talk
flag Dynamic Bayesian Networks for Multimodal Interaction
as author at  2nd Joint Workshop on Multimodal Interaction and Related Machine Learning Algorithms, Edinburgh 2005,
10481 views
  lecture
flag Spectral Clustering and Embedding with Hidden Markov Models
as author at  European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD), Warsaw 2007,
7131 views
invited talk
flag Multi-Task Discriminative Estimation for Generative Models and Probabilities
as author at  Generative / Discriminative Interface,
5472 views
  lecture
flag Graph Construction and b-Matching for Semi-Supervised Learning
as author at  Sessions,
5682 views
lecture
flag MAP Estimation with Perfect Graphs
as author at  Machine Learning Summer School (MLSS), Chicago 2009,
5570 views