photo of Jeffrey A. Bilmes
 
Jeffrey A. Bilmes
    University of Washington

Username:bilmes
 
 
 
 
Home page:http://melodi.ee.washington.edu/people/bilmes/pgs/index.html
Bio:  Jeff A. Bilmes is a professor in 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 the founder of the MELODI (MachinE Learning for Optimization and Data Interpretation) lab. He received his Ph.D. from the Computer Science Division of the department of EECS at UC Berkeley.

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 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 also has interests in high performance computing systems, computer architecture, and software techniques to reduce power consumption.

Papers, Presentations and Reports Authored by Jeffrey A. Bilmes

  1. Yr 5 Quarterly Report #4 (August 1, 2017 - October 31, 2017) Milestone 23, Jeffrey A. Bilmes, Prabal Dutta, Richard Murray, Anthony Rowe, Alberto Sangiovanni-Vincentelli, Sanjit Seshia, November, 2017. Posted on 29 Nov 2017.
  2. Deep Submodular Data, Jeffrey A. Bilmes, 12, October, 2017. Posted on 10 Oct 2017.
  3. Yr 5 Quarterly Report #3 (May 1, 2017 - July 31, 2017) Milestone 22, Jeffrey A. Bilmes, Prabal Dutta, Richard Murray, Anthony Rowe, Alberto Sangiovanni-Vincentelli, Sanjit Seshia, August, 2017. Posted on 30 Aug 2017.
  4. Yr 5 Quarterly Report #2 (Feb 1, 2017 - Apr 30, 2017) Milestone 21, Jeffrey A. Bilmes, Prabal Dutta, Richard Murray, Anthony Rowe, Alberto Sangiovanni-Vincentelli, Sanjit Seshia, April, 2017. Posted on 30 May 2017.
  5. Plenary Session #2, Jeffrey A. Bilmes, 27, October, 2016. Posted on 26 Sep 2016.
  6. GMTK Tutorial: The Graphical Models Toolkit, Jeffrey A. Bilmes, 16, September, 2016. Posted on 12 Jul 2016.
  7. Machine Learning in Urban Heartbeat, Jeffrey A. Bilmes, 13, January, 2016. Posted on 13 Jan 2016.
  8. Information Overload, Jeffrey A. Bilmes, 15, October, 2015. Posted on 15 Oct 2015.
  9. TerraSwarm 2015 Annual Meeting: Theme 3: Services and Cloud Interactions, Jeffrey A. Bilmes, Anthony Rowe, 14, October, 2015. Posted on 5 Oct 2015.
  10. Summarizing Large Data Sets, Jeffrey A. Bilmes, 20, August, 2015. Posted on 30 Jul 2015.
  11. Q1 2015 TerraSwarm Quarterly Report Milestone #10, Edward A. Lee, Tajana Simunic Rosing, John Wawrzynek, Prabal Dutta, Anthony Rowe, Richard Murray, Jeffrey A. Bilmes, Alberto Sangiovanni-Vincentelli, Sanjit Seshia, Jan Rabaey, Douglas L. Jones, Stephane Lafortune, Alex Halderman, David Blaauw, Roozbeh Jafari, Carlos Guestrin, Emily B. Fox, Rahul Mangharam, George Pappas, Vijay Kumar, Bjoern Hartmann, John D. Kubiatowicz, TerraSwarm Research Center, February, 2015. Posted on 25 Feb 2015.
  12. GMTK: The Graphical Models Toolkit, Jeffrey A. Bilmes, Richard Rogers, University of Washington, 10, February, 2015. Posted on 10 Feb 2015.
  13. Submodular Point Processes with Applications to Machine Learning, Rishabh Iyer, Jeffrey A. Bilmes, International Conference on Artificial Intelligence and Statistics, 9, May, 2015. Posted on 9 Feb 2015.
  14. Divide-and-Conquer Learning by Anchoring a Conical Hull, Tianyi Zhou, Jeffrey A. Bilmes, Carlos Guestrin, October, 2014. Posted on 4 Nov 2014.
  15. Divide-and-Conquer Learning by Anchoring a Conical Hull, Tianyi Zhou, Jeffrey A. Bilmes, Carlos Guestrin, Neural Information Processing Systems Conference (NIPS), December, 2014. Posted on 3 Nov 2014.
  16. Summarization of and Learning in TerraSwarm Big Data, Jeffrey A. Bilmes, 30, October, 2014. Posted on 28 Oct 2014.
  17. Online Activity Inference with GMTK, Jeffrey A. Bilmes, Richard Rogers, 29, October, 2014. Posted on 28 Oct 2014.

Counts

  • 4 Conference papers.
  • 1 Technical report.
  • 9 Talk or presentations.
  • 9 Posters.
  • 3 Unpublished articles.
  • 1 Software.
  • 2 Tutorials.

The counts above are from the publications database. The number of posters is derived from the presentations.

Note: A poster is a presentation that has the word 'poster' (case-insensitive) in the any of the text fields. Thus, the poster count might be somewhat inaccurate. The number of posters is deducted from the number of presentations and bother are reported.