JEFF 2011
  • Professor, School Of Computing

Publications

Presentations

  • Matrix Sketching: Large-Scale Matrix Computation. HEAP Seminar, Physics & Astronomy, University of Utah. Invited Talk/Keynote, Presented, 01/2015.
  • Improved Practical Matrix Sketching with Guarantees. 22nd Annual European Symposium on Algorithms (ESA), September, 2014. Conference Paper, Refereed, Presented, 09/2014.
  • Deterministic (Distributed) Streaming Matrix Approximation. Computer Science Colloquium at Ohio State University. Invited Talk/Keynote, Presented, 07/2014.
  • Large Scale Kernel Density Estimates: Smoother is Better. Big Data Workshop at CUHK. Invited Talk/Keynote, Presented, 07/2013.
  • eps-Samples for Kernels. Jeff M. Phillips. 24th Annual ACM-SIAM Symposium on Discrete Algorithms (SoDA). January 2013. Conference Paper, Refereed, Presented, 01/2013.
  • Efficient Protocols for Distributed Classification and Optimization. Hal Daume III, Jeff M. Phillips, Avishek Saha, and Suresh Venkatasubramanian. 23rd International Conference on Algorithmic Learning Theory (ALT). October 2012. Conference Paper, Refereed, Presented, 10/2012.
  • Mergeable Summaries. Pankaj K. Agarwal, Graham Cormode, Zengfeng Huang, Jeff M. Phillips, Zhewei Wei, and Ke Yi. 31st ACM Symposium on Principals of Database Systems (PODS). May 2012. Conference Paper, Refereed, Presented, 05/2012.
  • Mergeable Summaries. NII Shonan Meeting on Large Scale Distributed Data. Invited Talk/Keynote, Presented, 01/2012.
  • Computational Geometry on Uncertain Data. Joint Math Meeting: SIAM Minisymposium on Computational Geometry. Invited Talk/Keynote, Presented, 01/2012.
  • Comparing Distributions and Shapes with the Kernel Distance. Peking University, Beijing, China. Invited Talk/Keynote, Presented, 08/2011.
  • Handling Uncertainty in Spatial Data. Computer Science Department, The Ohio State University. Invited Talk/Keynote, Presented, 08/2011.
  • Measuring Data Sets under Uncertainty. Yahoo! Labs. Invited Talk/Keynote, Presented, 04/2011.
  • Accounting for Error in Large Data Sets. Computer Science, Texas A&M University. Invited Talk/Keynote, Presented, 03/2011.
  • Accounting for Error in Large Data Sets. School of Computing, University of Utah. Invited Talk/Keynote, Presented, 03/2011.
  • Comparing Distributions and Shapes with the Kernel Distance. MADALGO and Computer Science Department, Aarhus University. Invited Talk/Keynote, Presented, 09/2010.
  • Sampling from Probe-Only Distributions. Computer Science Department, Duke University. Invited Talk/Keynote, Presented, 04/2010.
  • Matching Shapes using the Current Distance. Computer Science Department. Institute for Science and Technology, Austria. Invited Talk/Keynote, Presented, 09/2009.
  • Algorithms for eps-Samples of Terrains. MADALGO and Computer Science Department, Aarhus University. Invited Talk/Keynote, Presented, 09/2008.
  • Maximizing Statistical Discrepancy. Statistical and Applied Mathematical Science Institute, RTP, NC. Invited Talk/Keynote, Presented, 02/2006.
  • On Maximizing Statistical Discrepancy. AT&T: Shannon Labs. Invited Talk/Keynote, Presented, 08/2005.
  • Probabilistic Network Optimization Applied To Spacecraft Rendezvous & Docking. NASA, Johnson Space Center. Invited Talk/Keynote, Presented, 08/2003.
  • Probabilistic Network Optimization Applied to Spacecraft Rendezvous & Docking. C. S. Draper Laboratories. Invited Talk/Keynote, Presented, 09/2002.

Research Groups

  • Mingxuan Han, Graduate Student. 01/01/2019 - present.
  • Giorgi Kvernadze, Undergraduate Student. Computing. 08/2017 - 08/15/2018.
  • Safia Hassan, Undergraduate Student. Computer Science. 12/2016 - 12/2017.
  • Zahra Fahimfar, Graduate Student. Computing. 03/2016 - 05/15/2018.
  • Tami Porter-Jones, Undergraduate Student. School of Computing. 09/2014 - 05/2015.
  • Tony Tuttle, Undergraduate Student. School of Computing. 06/2014 - 08/2014.
  • Jamie Iong, Undergraduate Student. School of Computing. 06/2014 - 05/2015.