Former Students of Jeff Phillips
Yanqing Peng (PhD 2022, co-advised by Feifei Li)
Toward Designing Efficient and Secure Systems for Big Data
| first job @ Meta
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At-the-time and Back-in-time Persistent Sketches.
Benwei Shi, Zhuoyue Zhao, Yanqing Peng, Feifei Li, and Jeff M. Phillips.
ACM Symposium on Management of Data (SIGMOD). June 2021.
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Constrained Non-Affine Alignment of Embeddings.
Yuwei Wang, Yan Zheng, Yanqing Peng, Michael Yeh, Zhongfang Zhuang, Das Mahashweta, Bendre Mangesh, Feifei Li, Wei Zhang, and Jeff M. Phillips.
International Conference on Data Mining (ICDM).
December 2021.
arXiv:1910.05862.
September 2021.
- (and several other without me, not listed)
Yuwei Wang (MS 2021, co-advised by Feifei Li)
| first job @ Facebook
Zhuoyue Zhao (PhD 2021, co-adivsed by Feifei Li)
Approximate Query Processing via Random Sampling
| first job @ Assistant Prof @ U. Buffalo
Zhao Chang (PhD 2021, co-adivsed by Feifei Li)
Scalable and Secure Data Analysis in Cloud
| first job @ faculty at Xidan University
Austin Watkins (BS Thesis 2020) Using Existential Theory of the Reals to Bound VC-Dimension
| first job @ PhD student and Johns Hopkins CS
Sunipa Dev (PhD 2020) The Geometry of Distributed Representations for Better Alignment, Attenuated Bias, and Improved Interpretability | first job NSF CI Posdoctoral Fellow @ UCLA.
Wai Ming Tai (PhD 2020) Geometry of Kernel Density Estimate | first job postdoc @ UChicago.
Jiahui (Karen) Chen (BS Thesis 2020) Practical and Configurable Network Traffic Classification using Probabilistic Machine Learning
| first job @ Facebook
Michael Matheny (PhD 2019) Approximate Statistical Discrepancy | first job @ Amazon.
Pingfan Tang (PhD 2019) Robust Estimation and Sketching of Points, Lines, Trajectories and other Shapes | first job @ Google.
Stone Mele (BS)
| first job @ MS student in Computing @ UofU
Jian Ying (MS Thesis 2019) Corrected Moran's I Statistic
| first job @ Biostatisticial at the Huntsman Cancer Institute
Zahra Fahimfar (MS Thesis 2018) Detecting Potential Lensed Galaxies Behind Foreground Galaxy Targets Using Machine Learning Techniques
Giorgi Kvernadze (BS Thesis 2018) Data-Driven Secret Santa | first job @ MS student in Computing @ UofU.
Roy Y. Wong (MS Thesis 2017) Moran's I Spatial Auto-Correlation and Anomaly Detection Utilizing PCA and High Dimensional Feature Vectors
Safia Hassan (BS Thesis 2017) Evaluating the Relationship between Vector Spaces of Word Embeddings | first job @ MS student in Computing at UofU.
Mina Ghashami (PhD 2017) On FrequentDirections | first job @ Rutgers CS as postdoc --> Visa Research.
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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.
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Streaming Kernel Principal Component Analysis.
Mina Ghashami, Daniel Perry, and Jeff M. Phillips.
International Conference on Artificial Intelligence and Statistics (AISTATS).
May 2016.
arxiv.org:1512.05059.
December 2015.
Julia Code.
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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.
2016.
earlier shorter version appeared in
22nd Annual European Symposium on Algorithms (ESA).
September 2014.
Reproduce our results on APTlab. (You may need to log in, and then click link again)
arXiv:1501.06561.
January 2015.
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Continuous Matrix Approximation on Distributed Data.
Mina Ghashami, Jeff M. Phillips, and Feifei Li.
40th International Conference on Very Large Data Bases (VLDB).
September 2014.
full version: arXiv:1404.7571.
April 2014.
Python Code.
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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.
Python Code, with some backend in C.
this mainly extends and replaces:
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.
Yan Zheng (PhD 2017) Algorithms and Coresets for Large Scale Kernel Smoothing | first job @ Visa Research
Drew McClelland (BS Thesis 2017) Analysis of Mapping Techniques on a Spatial Scan Statistic | first job @ Qualtrics
Yi Oi (MS 2017) Visualization of Large Scale Spatial Data Using Kernel Density Estimates | first job @ Expedia
Sierra Allred (BS Thesis 2016) College Cost Analyzer: Pick Want You Can Pay For | first job @ MS program in Utah SoC
KaiQiang Wang (MS 2016) Stability of the Null Distribution for Spatial Scan Statistics | first job @ Google
Liang Zhang (MS 2015) Stability of Spatial Scan Statistics | first job @ Microsoft
Raghvendra Singh (MS Thesis 2015) Scalable Spatial Scan Statistics | first job @ InsideSales
Jamie Iong (BS Thesis 2015) Solving K-depth Coverage problem using Sweep Line Algorithm and Red Black Tree | first job @ EMC
Tami Porter-Jones (BS Thesis 2015) Detecting Large DNA Rearrangements Using NGS Data | first job @ Myriad Genetics
Amey Desai (MS Thesis 2014) Streaming Algorithms for Matrix Approximation | first job @ UrbanEngines (Bay Area startup) -> Google
Shashanka Krishnaswamy (MS 2013) Quality Control in Weather Updates Via Quantiles | first job @ Amazon
Supraja Jayakumar (MS 2013) Uncertain Centerpoints | first job @ Cerner Systems
Alex Clemmer (BS Thesis 2013) Streaming LDA | first jobs @ Hacker's School + Microsoft
In 2017 Alex's paper was awarded best paper at ACM SIGIR!