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Professor, School Of Computing
Publications
- Tao Yang, Cuize Han, Chen Luo, Parth Gupta, Jeff M. Phillips, and Qingyao Ai (2024). Mitigating Exploitation Bias in Learning to Rank with an Uncertainty-aware Empirical Bayes Approach. The Web Conference (WWW).
Published, 05/2024.
- Archit Rathore, Sunipa Dev, Jeff M. Phillips, Vivek Srikumar, Yan Zheng, Chin-Chia Michael Yeh, Junp (2024). VERB: Visualizing and Interpreting Bias Mitigation Techniques for Word Representations. ACM Transactions on Interactive Intelligent Systems.
Published, 01/2024.
- Peyman Afshani and Jeff M. Phillips (2019). Independent Range Sampling, Revisited Again. International Symposium on Computational Geometry (SoCG).
Published, 06/2019.
https://arxiv.org/abs/1903.08014
- Anne Driemel, Jeff M. Phillips, Ioannis Psarros (2019). On the VC Dimension of Metric Balls under Frechet and Hausdorff Distances. International Symposium on Computational Geometry (SoCG).
Published, 06/2019.
https://arxiv.org/abs/1903.03211
- Sunipa Dev and Jeff M. Phillips (2019). Attenuating Bias in Word Vectors. International Conference on Artificial Intelligence and Statistics (AIStats).
Published, 04/2019.
https://arxiv.org/abs/1901.07656
- Michael Matheny and Jeff M. Phillips (2018). Computing Approximate Statistical Discrepancy. International Symposium on Algorithm and Computation (ISAAC).
Published, 12/2018.
https://arxiv.org/abs/1804.11287
- Ryan Baker, Ren Quinn, and Jeff M. Phillips, Jacobus (Kobus) Van der Merwe (2018). Toward Classifying Unknown Application Traffic. DYnamic and Novel Advances in Machine Learning and Intelligent Cyber Security (DYNAMICS) Workshop.
Published, 12/2018.
http://www.cs.utah.edu/~jeffp/papers/283.pdf
- Aria Rezaei, Jie Gao, Jeff M. Phillips, and Csaba D. Toth (2018). Improved Bounds on Information Dissemination by Manhattan Random Waypoint Model. ACM International Conference on Advances in Geographic Information Systems (SIGSPATIAL).
Published, 11/2018.
https://arxiv.org/abs/1809.07392
- Michael Matheny and Jeff M. Phillips (2018). Practical Low-Dimensional Halfspace Range Space Sampling. European Symposium on Algorithms (ESA).
Published, 09/2018.
https://arxiv.org/abs/1804.11307
- Pingfan Tang, Kevin Buchin & Jeff M. Phillips (2018). Approximating the Distribution of the Median and other Robust Estimators on Uncertain Data. International Symposium on Computational Geometry (SOCG).
Published, 06/2018.
https://arxiv.org/abs/1601.00630
- Wai Ming Tai & Jeff M. Phillips (2018). Near-Optimal Coresets of Kernel Density Estimates. International Symposium on Computational Geometry (SOCG).
Published, 06/2018.
https://arxiv.org/abs/1802.01751
- Yang Gao, Jeff M. Phillips, Yan Zheng, Renqiang Min, P. Thomas Fletcher & Guido Gerig (2018). Fully Convolutional Structured LSTM Networks for Joint 4D Medical Image Segmentation. IEEE International Symposium on Biomedical Imaging (ISBI).
Published, 04/2018.
http://www.cs.utah.edu/~jeffp/papers/ISBI18.pdf
- Wai Ming Tai & Jeff M. Phillips (2018). Improved Coresets for Kernel Density Estimates. ACM-SIAM Symposium on Discrete Algorithms (SoDA).
Published, 01/2018.
https://arxiv.org/abs/1710.04325
- Tim Sodergren, Jessica Hair, Jeff M. Phillips & Bei Wang (2017). Visualizing Sensor Network Coverage with Location Uncertainty. Visual Data Science (VDS).
Published, 10/2017.
https://arxiv.org/abs/1710.06925
- Yan Zheng, Yi Ou, Alexander Lex & Jeff M. Phillips (2017). Visualization of Big Spatial Data using Coresets for Kernel Density Estimates. Visual Data Science (VDS).
Published, 10/2017.
https://arxiv.org/abs/1709.04453
- Di Chen & Jeff M. Phillips (2017). Relative Error Embeddings for the Gaussian Kernel Distance. Algorithmic Learning Theory (ALT).
Published, 10/2017.
https://arxiv.org/abs/1602.05350
- Yan Zheng & Jeff M. Phillips (2017). Coresets for Kernel Regression. ACM Conference on Knowledge Discovery and Data Mining (KDD).
Published, 08/2017.
https://arxiv.org/abs/1702.03644
- Dong Xie, Jeff M. Phillips & Feifei Li (2017). Distributed Trajectory Similarity Search. International Conference on Very Large Databases (VLDB).
Published, 08/2017.
http://www.cs.utah.edu/~jeffp/papers/trajvldb17.pd...
- The Robustness of Estimator Composition. Pingfan Tang and Jeff M. Phillips. Conference on Neural Information Processing (NIPS). December 2016.
Published, 12/2016.
- Scalable Spatial Scan Statistics through Sampling. Michael Matheny, Raghvendra Singh, Kaiqiang Wang, Liang Zhang and Jeff M. Phillips. ACM International Conference on Advances in Geographic Information Systems (SIGSPATIAL). November 2016.
Published, 11/2016.
- epsilon-Kernel Coresets for Stochastic Points. Lingxiao Huang, Jian Li, Jeff M. Phillips, and Haitao Wang. European Symposium on Algorithms (ESA). August 2016. arxiv.org:1411.0194. November 2014.
Published, 08/2016.
- Efficient Frequent Directions Algorithm for Sparse Matrices. Mina Ghashami, Edo Liberty, and Jeff M. Phillips. ACM Conference on Knowledge Discovery and Data Mining (KDD). August 2016. arxiv.org:1602.00412. February 2016.
Published, 08/2016.
- Frequent Directions: Simple and Deterministic Matrix Sketching. Mina Ghashami, Edo Liberty, Jeff M. Phillips and David P. Woodruff. SIAM Journal of Computing (SICOMP) 45:5, 2016. arXiv:1501.01711. January 2015.
Published, 08/2016.
- An Integrated Classification Scheme for Mapping Estimates and Errors of Estimation from the American Community Survey. Ran Wei, Daoqin Tong, and Jeff M. Phillips. Computers, Environment and Urban Systems (CEUS). April 2016.
Published, 04/2016.
- Improved Practical Matrix Sketching with Guarantees. Mina Ghashami, Amey Desai, and Jeff M. Phillips. Transactions on Knowledge and Data Engineering (TKDE) 28:07, pp 1678--1690, 2016. earlier shorter version appeared in 22nd Annual European Symposium on Algorithms (ESA). September 2014. arXiv:1501.06561. January 2015.
Published, 02/2016.
- Lower Bounds for Number-in-Hand Multiparty Communication Complexity, Made Easy. Jeff M. Phillips, Elad Verbin, Qin Zhang. SIAM Journal of Computing (SICOMP) 45; 174-196. 2016. arXiv:1107.2559. July 2011.
Published, 02/2016.
- Subsampling in Smooth Range Spaces. Jeff M. Phillips and Yan Zheng. Algorithmic Learning Theory (ALT). October 2015. short version appeared in Computational Geometry : Young Researchers Forum. June 2015.
Published, 10/2015.
- L_infity Error and Bandwidth Selection for Kernel Density Estimates of Large Data. Yan Zheng and Jeff M. Phillips. ACM Conference on Knowledge Discovery and Data Mining (KDD). August 2015.
Published, 08/2015.
- Geometric Inference on Kernel Density Estimates. Jeff M. Phillips, Bei Wang, and Yan Zheng. International Symposium on Computational Geometry (SoCG), 2015. arXiv:1307.7760, January, 2014.
Published, 06/2015.
- Continuous Matrix Approximation on Distributed Data. Mina Ghashami, Jeff M. Phillips, and Feifei Li. 40th International Conference on very Large Data Bases (VLDB), 2014. arXiv:1404.7571. April 2014.
Published, 09/2014.
- Improved Practical Matrix Sketching with Guarantees. Mina Ghashami, Amey Desai, and Jeff M. Phillips. 22nd Annual European Symposium on Algorithms (ESA), 2014.
Published, 09/2014.
- Relative Errors for Deterministic Low-Rank Matrix Approximations. Mina Ghashami and Jeff M. Phillips. 25th Annual ACM-SIAM Symposium on Discrete Algorithms (SoDA). January 2014. arXiv:1307.7454. June 2013.
Published, 01/2014.
- Mergeable Summaries. Pankaj K. Agarwal, Graham Cormode, Zengfeng Huang, Jeff M. Phillips, Zhewei Wei, and Ke Yi. ACM Transactions on Database Systems (TODS) 38:26, 2013.
Published, 11/2013.
- Quality and Efficiency for Kernel Density Estimates in Large Data. Yan Zheng, Jeffrey Jestes, Jeff M. Phillips, Feifei Li. ACM Conference on the Management of Data (SIGMOD). June 2013.
Published, 06/2013.
- Range Counting Coresets for Uncertain Data. Amirali Abdullah, Samira Daruki, and Jeff M. Phillips. 29th Annual ACM Symposium on Computational Geometry (SoCG). June 2013.
Published, 06/2013.
- Nearest Neighbor Searching Under Uncertainty II. Pankaj K. Agarwal, Boris Aronov, Sariel Har-Peled, Jeff M. Phillips, Ke Yi, and Wuzhou Zhang. 32nd ACM Symposium on Principles of Database Systems (PoDS). June 2013.
Published, 06/2013.
- Radio Tomographic Imaging and Tracking of Stationary and Moving People via Kernel Distance. Yang Zhao, Neal Patwari, Jeff M. Phillips, and Suresh Venkatasubramanian. 12th ACM-IEEE Conference on Information Processing in Sensor Networks (IPSN). April 2013.
Published, 04/2013.
- eps-Samples for Kernels. Jeff M. Phillips. 24th Annual ACM-SIAM Symposium on Discrete Algorithms (SoDA). January 2013.
Published, 01/2013.
- (Approximate) Uncertain Skylines. Peyman Afshani, Pankaj K. Agarwal, Lars Arge, Kasper Green Larsen, and Jeff M. Phillips. Theory of Computing Systems 52, 342--366 (Special Issue : ICDT 2011) 2013.
Published, 01/2013.
- Sensor Network Localization for Moving Sensors. Arvind Agarwal, Hal Daume III, Jeff M. Phillips, and Suresh Venkatasubramanian.2nd IEEE ICDM International Workshop on Data Mining in Networks (DaMNet). December 2012.
Published, 12/2012.
- 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.
Published, 10/2012.
- Ranking Large Temporal Data. Jeffrey Jestes, Jeff M. Phillips, Feifei Li, and Mingwang Tang. 38th International Conference on Very Large Databases (VLDB). August 2012. PVLDB 5:1412-1423, 2012.
Published, 08/2012.
- 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).
Published, 05/2012.
http://www.cs.utah.edu/~jeffp/papers/mergeSumm.pdf
- Efficient Threshold Monitoring for Distributed Probabilistic Data. Mingwang Tang, Feifei Li, Jeff M. Phillips, Jeffrey Jestes. 28th IEEE International Conference on Data Engineering (ICDE). April 2012.
Published, 04/2012.
- Uncertainty Visualization in HARDI based on Ensembles of ODFs. Fangxiang Jiao, Jeff M. Phillips, Yaniv Gur, and Chris R. Johnson. 5th IEEE Pacific Visualization Symposium (PacificVis).
Published, 02/2012.
http://www.cs.utah.edu/~jeffp/papers/uncertainHARD...
- Lower Bounds for Number-in-Hand Multiparty Communication Complexity, Made Easy. Jeff M. Phillips, Elad Verbin, Qin Zhang. 23th Annual ACM-SIAM Symposium on Discrete Algorithms (SoDA).
Published, 01/2012.
http://arxiv.org/abs/1107.2559
- Generating A Diverse Set Of High-Quality Clusterings. Jeff M. Phillips, Parasaran Raman, Suresh Venkatasubramanian. 2nd MultiClust Workshop: Discovering, Summarizing and Using Multiple Clusterings (MultiClust).
Published, 09/2011.
http://www.cs.utah.edu/~jeffp/papers/alternative.p...
- Horoball Hulls and Extents in Positive Definite Space. P. Thomas Fletcher, John Moeller, Jeff M. Phillips, Suresh Venkatasubramanian. 12th Algorithms and Data Structure Symposium (WADS).
Published, 08/2011.
http://www.cs.utah.edu/~jeffp/papers/PDn.pdf
- Geometric Computation on Indecisive Points. Allan G. Jorgensen, Maarten Loffler, Jeff M. Phillips. 12th Algorithms and Data Structure Symposium (WADS).
Published, 08/2011.
http://www.cs.utah.edu/~jeffp/papers/indecisive-lo...
- Comparing Distributions and Shapes Using the Kernel Distance. Sarang Joshi, Raj Varma Kommaraju, Jeff M. Phillips, Suresh Venkatasubramanian. 27th Annual Symposium on Computational Geometry (SoCG).
Published, 06/2011.
http://www.cs.utah.edu/~jeffp/papers/arXiv1001.059...
- Spatially-Aware Comparison and Consensus for Clusterings. Jeff M. Phillips, Parasaran Raman, and Suresh Venkatasubramanian. 10th SIAM Intenational Conference on Data Mining (SDM).
Published, 04/2011.
http://www.cs.utah.edu/~jeffp/papers/liftCluster-S...
- (Approximate) Uncertain Skylines. Peyman Afshani, Pankaj K. Agarwal, Lars Arge, Kasper Green Larsen, and Jeff M. Phillips. 14th International Conference on Database Theory (ICDT).
Published, 03/2011.
http://www.cs.utah.edu/~jeffp/papers/uncert-skylin...
- Stability of epsilon-Kernels. Pankaj K. Agarwal, Jeff M. Phillips, Hai Yu. 18th Annual European Symposium on Algorithms (ESA).
Published, 09/2010.
http://www.cs.utah.edu/~jeffp/papers/arXiv1003.587...
- Metrics for Uncertainty Analysis and Visualization of Diffusion Tensor Images. Fangxiang Jiao, Jeff M. Phillips, Jeroen Stinstra, Jens Krueger, Raj Varma Kummaraju, Edward Hsu, Julie Korenberg, Chris R. Johnson. 5th International Workshop on Medical Imaging and Augmented Reality (MIAR).
Published, 09/2010.
http://www.cs.utah.edu/~jeffp/papers/fiber-uncerta...
- Universal Multi-Dimensional Scaling. Arvind Agarwal, Jeff M. Phillips, Suresh Venkatasubramanian. 16th Annual ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD).
Published, 08/2010.
http://arxiv.org/abs/1003.0529
- Lipschitz Unimodal and Isotonic Regression on Paths and Trees. Pankaj K. Agarwal, Jeff M. Phillips, Bardia Sadri. 9th Latin American Theoretical Informatics Symposium (LATIN).
Published, 04/2010.
http://www.cs.utah.edu/~jeffp/papers/arXiv0912.518...
- Shape Fitting on Point Sets with Probability Distributions. Maarten Loffler, Jeff M. Phillips. 17th Annual European Symposium on Algorithms (ESA). September.
Published, 09/2009.
http://www.cs.utah.edu/~jeffp/papers/uncertaintyES...
- Algorithms for epsilon-Approximations of Terrains. (Best Student Paper) Jeff M. Phillips. 35th International Colloquium on Automata, Languages, and Programming (ICALP).
Published, 07/2009.
http://www.cs.utah.edu/~jeffp/papers/arXiv0801.279...
- An Efficient Algorithm for Euclidean 2-Center with Outliers. Pankaj K. Agarwal, Jeff M. Phillips. 16th Annual European Symposium on Algorithms (ESA).
Published, 09/2008.
http://www.cs.utah.edu/~jeffp/papers/arXiv0806.432...
- Spatial Scan Statistics for Graph Clustering. Bei Wang, Jeff M. Phillips, Robert Schrieber, Dennis Wilkinson, Nina Mishra, Robert Tarjan. 8th SIAM Intenational Conference on Data Mining (SDM).
Published, 04/2008.
http://www.cs.utah.edu/~jeffp/papers/SSSGC-SDM08.p...
- Value-Based Notification Conditions in Large-Scale Publish/Subscribe Systems. Badrish Chandramouli, Jeff M. Phillips, Jun Yang. 33rd Intenational Conference on Very Large Data Bases (VLDB).
Published, 09/2007.
http://www.cs.utah.edu/~jeffp/papers/VBNCinLSPSS-V...
- Outlier Robust ICP for Minimizing Fractional RMSD. Jeff M. Phillips, Ran Liu, Carlo Tomasi. 6th International Conference on 3-D Digital Imaging and Modeling (3DIM). August 2007.
Published, 08/2007.
http://www.cs.utah.edu/~jeffp/papers/FICPtr-CS-200...
- Segmenting Motifs in Protein-Protein Interface Surfaces. Jeff M. Phillips, Johannes Rudolph, Pankaj K. Agarwal. Proceedings of the 6th Workshop on Algorithms in Bioinformatics (WABI).
Published, 09/2006.
http://www.cs.utah.edu/~jeffp/papers/motifs-WABI06...
- Spatial Scan Statistics: Approximations and Performance Study. Deepak Agarwal, Andrew McGregor, Jeff M. Phillips, Suresh Venkatasubramanian, Zhengyuan Zhu. 12th Annual ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD).
Published, 08/2006.
http://www.cs.utah.edu/~jeffp/papers/stat-disc-KDD...
- On Bipartite Matching under the RMS Distance. Pankaj K. Agarwal, Jeff M. Phillips. 18th Canadian Conference on Computational Geometry (CCCG).
Published, 08/2006.
http://www.cs.utah.edu/~jeffp/papers/rms-bipartite...
- The Hunting of the Bump: On Maximizing Statistical Discrepancy. Deepak Agarwal, Jeff M. Phillips, Suresh Venkatasubramanian. 17th Annual ACM-SIAM Symposium on Discrete Algorithms (SoDA).
Published, 01/2006.
http://www.cs.utah.edu/~jeffp/papers/stat-disc-SOD...
- Guided Expansive Spaces Trees: A Search Strategy for Motion- and Cost-Constrained State Spaces. Jeff M. Phillips, Nazareth Bedrossian, and Lydia E. Kavraki. IEEE International Conference on Robotics and Automation (ICRA).
Published, 04/2004.
http://www.cs.utah.edu/~jeffp/papers/guidedESTs_IC...
- Simulated Knot Tying. Jeff M. Phillips, Andrew M. Ladd, Lydia E. Kavraki. IEEE International Conference on Robotics and Automation (ICRA).
Published, 05/2002.
http://www.cs.utah.edu/~jeffp/papers/rope-icra.pdf
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.