Jeff A. Bilmes
homepage:http://ssli.ee.washington.edu/~bilmes/pgs/index.html
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Description

Jeff A. Bilmes is a professor at the Department of Electrical Engineering at the University of Washington, Seattle Washington. He is also an adjunct professor in Computer Science & Engineering and the department of Linguistics. He is also the founder of the MELODI (MachinE Learning for Optimization and Data Interpretation) lab here in the department. He received his Ph.D. from the Computer Science Division of the department of Electrical Engineering and Computer Science, University of California in Berkeley. He was also a researcher at the International Computer Science Institute, and a member of the Realization group there.

He is a 2001 NSF Career award winner, a 2002 CRA Digital Government Fellow, and a 2008 NAE Gilbreth Lectureship award recipient

His primary interests lie in statistical modeling (particularly graphical model approaches) and signal processing for pattern classification, speech recognition, language processing, bioinformatics, machine learning, submodularity in combinatorial optimization and machine learning, active and semi-supervised learning, and audio/music processing. He is particularly interested in temporal graphical models (or dynamic graphical models, which includes HMMs, DBNs, and CRFs) and ways in which to design efficient algorithms for them and design their structure so that they may perform as better structured classifiers. He also has strong interests in speech-based human-computer interfaces, the statistical properties of natural objects and natural scenes, information theory and its relation to natural computation by humans and pattern recognition by machines, and computational music processing (such as human timing subtleties). He is also quite interested in high performance computing systems, computer architecture, and software techniques to reduce power consumption.


Lectures:

introduction
flag Introduction to Jack EdmondsĀ“s talk
as author at  Discrete Optimization in Machine Learning,
4623 views
  lecture
flag Large-Scale Graph-based Transductive Inference
as author at  NIPS Workshops, Whistler 2009,
3671 views
demonstration video
flag Online Submodular Set Cover, Ranking, and Repeated Active Learning
as author at  Video Journal of Machine Learning Abstracts - Volume 2,
2513 views
  lecture
flag Summarizing Big Data: A Practical Use for Submodular Functions
as author at  NIPS Workshops, Lake Tahoe 2013,
1815 views