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Jeff M. Phillips
Person information

- affiliation: University of Utah, School of Computing
- affiliation: Duke University, Department of Computer Science
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2020 – today
- 2023
- [j23]Hasan Pourmahmood Aghababa, Jeff M. Phillips:
An experimental study on classifying spatial trajectories. Knowl. Inf. Syst. 65(4): 1587-1609 (2023) - [c82]Chin-Chia Michael Yeh
, Huiyuan Chen
, Xin Dai
, Yan Zheng
, Junpeng Wang
, Vivian Lai
, Yujie Fan
, Audrey Der
, Zhongfang Zhuang
, Liang Wang
, Wei Zhang
, Jeff M. Phillips
:
An Efficient Content-based Time Series Retrieval System. CIKM 2023: 4909-4915 - [c81]Prince Osei Aboagye, Yan Zheng, Jack Shunn, Chin-Chia Michael Yeh, Junpeng Wang, Zhongfang Zhuang, Huiyuan Chen, Liang Wang, Wei Zhang, Jeff M. Phillips:
Interpretable Debiasing of Vectorized Language Representations with Iterative Orthogonalization. ICLR 2023 - [c80]Mary W. Hall
, Ganesh Gopalakrishnan
, Eric Eide
, Johanna Cohoon
, Jeff M. Phillips
, Mu Zhang
, Shireen Y. Elhabian
, Aditya Bhaskara
, Harvey Dam
, Artem Yadrov
, Tushar Kataria
, Amir Mohammad Tavakkoli
, Sameeran Joshi
, Mokshagna Sai Teja Karanam
:
An NSF REU Site Based on Trust and Reproducibility of Intelligent Computation: Experience Report. SC Workshops 2023: 343-349 - [i75]Tao Yang, Cuize Han, Chen Luo, Parth Gupta, Jeff M. Phillips, Qingyao Ai:
Mitigating Exploitation Bias in Learning to Rank with an Uncertainty-aware Empirical Bayes Approach. CoRR abs/2305.16606 (2023) - [i74]Meysam Alishahi, Anna Little, Jeff M. Phillips:
Linear Distance Metric Learning with Noisy Labels. CoRR abs/2306.03173 (2023) - [i73]Jeff M. Phillips, Hasan Pourmahmood Aghababa:
For Kernel Range Spaces a Constant Number of Queries Are Sufficient. CoRR abs/2306.16516 (2023) - [i72]Mingxuan Han, Varun Shankar, Jeff M. Phillips, Chenglong Ye:
Locally Adaptive and Differentiable Regression. CoRR abs/2308.07418 (2023) - [i71]Chin-Chia Michael Yeh, Huiyuan Chen, Xin Dai, Yan Zheng, Junpeng Wang, Vivian Lai, Yujie Fan, Audrey Der, Zhongfang Zhuang, Liang Wang, Wei Zhang, Jeff M. Phillips:
An Efficient Content-based Time Series Retrieval System. CoRR abs/2310.03919 (2023) - [i70]Chin-Chia Michael Yeh, Yan Zheng, Menghai Pan, Huiyuan Chen, Zhongfang Zhuang, Junpeng Wang, Liang Wang, Wei Zhang, Jeff M. Phillips, Eamonn J. Keogh:
Sketching Multidimensional Time Series for Fast Discord Mining. CoRR abs/2311.03393 (2023) - [i69]Benwei Shi, Aditya Bhaskara, Wai Ming Tai, Jeff M. Phillips:
On Mergable Coresets for Polytope Distance. CoRR abs/2311.05651 (2023) - 2022
- [j22]Jiahui Chen
, Joe Breen, Jeff M. Phillips, Jacobus E. van der Merwe:
Practical and configurable network traffic classification using probabilistic machine learning. Clust. Comput. 25(4): 2839-2853 (2022) - [j21]Zhao Chang
, Dong Xie
, Feifei Li, Jeff M. Phillips, Rajeev Balasubramonian:
Efficient Oblivious Query Processing for Range and kNN Queries. IEEE Trans. Knowl. Data Eng. 34(12): 5741-5754 (2022) - [j20]Mingxuan Han, Chenglong Ye, Jeff M. Phillips:
Local Kernel Ridge Regression for Scalable, Interpolating, Continuous Regression. Trans. Mach. Learn. Res. 2022 (2022) - [c79]Prince Osei Aboagye, Yan Zheng, Chin-Chia Michael Yeh, Junpeng Wang, Zhongfang Zhuang, Huiyuan Chen, Liang Wang, Wei Zhang, Jeff M. Phillips:
Quantized Wasserstein Procrustes Alignment of Word Embedding Spaces. AMTA 2022: 200-214 - [c78]Austin Watkins, Jeff M. Phillips:
Using Existential Theory of the Reals to Bound VC Dimension. CCCG 2022: 314-321 - [c77]Zhao Chang
, Dong Xie
, Feifei Li, Jeff M. Phillips, Rajeev Balasubramonian:
Efficient and Oblivious Query Processing for Range and kNN Queries (Extended Abstract). ICDE 2022: 1487-1488 - [c76]Prince Osei Aboagye, Yan Zheng, Chin-Chia Michael Yeh, Junpeng Wang, Wei Zhang, Liang Wang, Hao Yang, Jeff M. Phillips:
Normalization of Language Embeddings for Cross-Lingual Alignment. ICLR 2022 - [c75]Shibo Li, Jeff M. Phillips, Xin Yu, Robert M. Kirby, Shandian Zhe:
Batch Multi-Fidelity Active Learning with Budget Constraints. NeurIPS 2022 - [i68]Hasan Pourmahmood Aghababa, Jeff M. Phillips:
Classifying Spatial Trajectories. CoRR abs/2209.01322 (2022) - [i67]Shibo Li, Jeff M. Phillips, Xin Yu, Robert M. Kirby, Shandian Zhe:
Batch Multi-Fidelity Active Learning with Budget Constraints. CoRR abs/2210.12704 (2022) - [i66]Prince Osei Aboagye, Yan Zheng, Chin-Chia Michael Yeh, Junpeng Wang, Zhongfang Zhuang, Huiyuan Chen, Liang Wang, Wei Zhang, Jeff M. Phillips:
Quantized Wasserstein Procrustes Alignment of Word Embedding Spaces. CoRR abs/2212.02468 (2022) - 2021
- [j19]Anne Driemel, André Nusser, Jeff M. Phillips, Ioannis Psarros
:
The VC Dimension of Metric Balls under Fréchet and Hausdorff Distances. Discret. Comput. Geom. 66(4): 1351-1381 (2021) - [j18]Kiran Gadhave
, Jochen Görtler, Zach Cutler, Carolina Nobre, Oliver Deussen, Miriah Meyer, Jeff M. Phillips, Alexander Lex
:
Predicting intent behind selections in scatterplot visualizations. Inf. Vis. 20(4) (2021) - [j17]Sunipa Dev
, Safia Hassan, Jeff M. Phillips:
Closed form word embedding alignment. Knowl. Inf. Syst. 63(3): 565-588 (2021) - [j16]Yan Zheng
, Yi Ou, Alexander Lex
, Jeff M. Phillips:
Visualization of Big Spatial Data Using Coresets for Kernel Density Estimates. IEEE Trans. Big Data 7(3): 524-534 (2021) - [j15]Zhiyan Yi, Xiaoyue Cathy Liu, Nikola Markovic, Jeff M. Phillips:
Inferencing hourly traffic volume using data-driven machine learning and graph theory. Comput. Environ. Urban Syst. 85: 101548 (2021) - [j14]Debjyoti Paul
, Feifei Li, Jeff M. Phillips:
Semantic embedding for regions of interest. VLDB J. 30(3): 311-331 (2021) - [c74]Benwei Shi, Jeff M. Phillips:
A Deterministic Streaming Sketch for Ridge Regression. AISTATS 2021: 586-594 - [c73]Sunipa Dev, Masoud Monajatipoor, Anaelia Ovalle, Arjun Subramonian, Jeff M. Phillips, Kai-Wei Chang:
Harms of Gender Exclusivity and Challenges in Non-Binary Representation in Language Technologies. EMNLP (1) 2021: 1968-1994 - [c72]Sunipa Dev, Tao Li, Jeff M. Phillips, Vivek Srikumar:
OSCaR: Orthogonal Subspace Correction and Rectification of Biases in Word Embeddings. EMNLP (1) 2021: 5034-5050 - [c71]Jasper C. H. Lee, Jerry Li, Christopher Musco, Jeff M. Phillips, Wai Ming Tai:
Finding an Approximate Mode of a Kernel Density Estimate. ESA 2021: 61:1-61:19 - [c70]Yuwei Wang, Yan Zheng, Yanqing Peng
, Chin-Chia Michael Yeh, Zhongfang Zhuang, Mahashweta Das, Mangesh Bendre, Feifei Li, Wei Zhang, Jeff M. Phillips:
Constrained Non-Affine Alignment of Embeddings. ICDM 2021: 1403-1408 - [c69]Michael Matheny, Jeff M. Phillips:
Approximate Maximum Halfspace Discrepancy. ISAAC 2021: 4:1-4:15 - [c68]Archit Rathore, Sunipa Dev, Jeff M. Phillips, Vivek Srikumar, Bei Wang:
A Visual Tour of Bias Mitigation Techniques for Word Representations. KDD 2021: 4064-4065 - [c67]Jeff M. Phillips, Hasan Pourmahmood Aghababa:
Orientation-Preserving Vectorized Distance Between Curves. MSML 2021: 472-496 - [c66]Archit Rathore, Sunipa Dev, Vivek Srikumar, Jeff M. Phillips, Yan Zheng, Chin-Chia Michael Yeh, Junpeng Wang, Wei Zhang, Bei Wang:
An Interactive Visual Demo of Bias Mitigation Techniques for Word Representations From a Geometric Perspective. NeurIPS (Competition and Demos) 2021: 330-335 - [c65]Zhimeng Pan, Zheng Wang, Jeff M. Phillips, Shandian Zhe:
Self-Adaptable Point Processes with Nonparametric Time Decays. NeurIPS 2021: 4594-4606 - [c64]Benwei Shi, Zhuoyue Zhao
, Yanqing Peng
, Feifei Li, Jeff M. Phillips:
At-the-time and Back-in-time Persistent Sketches. SIGMOD Conference 2021: 1623-1636 - [c63]Dong Xie
, Jeff M. Phillips, Michael Matheny, Feifei Li:
Spatial Independent Range Sampling. SIGMOD Conference 2021: 2023-2035 - [i65]Archit Rathore, Sunipa Dev, Jeff M. Phillips, Vivek Srikumar, Yan Zheng, Chin-Chia Michael Yeh, Junpeng Wang, Wei Zhang, Bei Wang:
VERB: Visualizing and Interpreting Bias Mitigation Techniques for Word Representations. CoRR abs/2104.02797 (2021) - [i64]Michael Matheny, Jeff M. Phillips:
Approximate Maximum Halfspace Discrepancy. CoRR abs/2106.13851 (2021) - [i63]Jiahui Chen, Joe Breen, Jeff M. Phillips, Jacobus E. van der Merwe:
Practical and Configurable Network Traffic Classification Using Probabilistic Machine Learning. CoRR abs/2107.06080 (2021) - [i62]Sunipa Dev, Masoud Monajatipoor, Anaelia Ovalle, Arjun Subramonian, Jeff M. Phillips, Kai-Wei Chang:
Harms of Gender Exclusivity and Challenges in Non-Binary Representation in Language Technologies. CoRR abs/2108.12084 (2021) - [i61]Mingxuan Han, Jeff M. Phillips, Sneha Kumar Kasera:
Hiding Signal Strength Interference from Outside Adversaries. CoRR abs/2112.10931 (2021) - [i60]Siu-Wing Cheng, Anne Driemel, Jeff M. Phillips:
Computational Geometry (Dagstuhl Seminar 21181). Dagstuhl Reports 11(4): 1-19 (2021) - 2020
- [j13]Jeff M. Phillips, Wai Ming Tai
:
Near-Optimal Coresets of Kernel Density Estimates. Discret. Comput. Geom. 63(4): 867-887 (2020) - [j12]Michael Matheny, Dong Xie
, Jeff M. Phillips:
Scalable Spatial Scan Statistics for Trajectories. ACM Trans. Knowl. Discov. Data 14(6): 73:1-73:24 (2020) - [c62]Sunipa Dev, Tao Li, Jeff M. Phillips, Vivek Srikumar:
On Measuring and Mitigating Biased Inferences of Word Embeddings. AAAI 2020: 7659-7666 - [c61]Jeff M. Phillips, Wai Ming Tai:
The GaussianSketch for Almost Relative Error Kernel Distance. APPROX-RANDOM 2020: 12:1-12:20 - [c60]Jeff M. Phillips, Pingfan Tang:
Sketched MinDist. SoCG 2020: 63:1-63:16 - [i59]Benwei Shi, Jeff M. Phillips:
A Deterministic Streaming Sketch for Ridge Regression. CoRR abs/2002.02013 (2020) - [i58]Sunipa Dev, Tao Li, Jeff M. Phillips, Vivek Srikumar:
OSCaR: Orthogonal Subspace Correction and Rectification of Biases in Word Embeddings. CoRR abs/2007.00049 (2020) - [i57]Jeff M. Phillips, Hasan Pourmahmood Aghababa:
Orientation-Preserving Vectorized Distance Between Curves. CoRR abs/2007.15924 (2020)
2010 – 2019
- 2019
- [c59]Sunipa Dev, Jeff M. Phillips:
Attenuating Bias in Word vectors. AISTATS 2019: 879-887 - [c58]Peyman Afshani, Jeff M. Phillips:
Independent Range Sampling, Revisited Again. SoCG 2019: 4:1-4:13 - [c57]Anne Driemel, Jeff M. Phillips, Ioannis Psarros
:
The VC Dimension of Metric Balls Under Fréchet and Hausdorff Distances. SoCG 2019: 28:1-28:16 - [c56]Mingxuan Han, Michael Matheny, Jeff M. Phillips:
The Kernel Spatial Scan Statistic. SIGSPATIAL/GIS 2019: 349-358 - [c55]Jeff M. Phillips, Pingfan Tang:
Simple Distances for Trajectories via Landmarks. SIGSPATIAL/GIS 2019: 468-471 - [c54]Sunipa Dev, Safia Hassan, Jeff M. Phillips:
Closed Form Word Embedding Alignment. ICDM 2019: 130-139 - [i56]Sunipa Dev, Jeff M. Phillips:
Attenuating Bias in Word Vectors. CoRR abs/1901.07656 (2019) - [i55]Anne Driemel, Jeff M. Phillips, Ioannis Psarros:
The VC Dimension of Metric Balls under Fréchet and Hausdorff Distances. CoRR abs/1903.03211 (2019) - [i54]Peyman Afshani, Jeff M. Phillips:
Independent Range Sampling, Revisited Again. CoRR abs/1903.08014 (2019) - [i53]Annie Cherkaev, Waiming Tai, Jeff M. Phillips, Vivek Srikumar:
Learning In Practice: Reasoning About Quantization. CoRR abs/1905.11478 (2019) - [i52]Michael Matheny, Dong Xie, Jeff M. Phillips:
Scalable Spatial Scan Statistics for Trajectories. CoRR abs/1906.01693 (2019) - [i51]Mingxuan Han, Michael Matheny, Jeff M. Phillips:
The Kernel Spatial Scan Statistic. CoRR abs/1906.09381 (2019) - [i50]Jeff M. Phillips, Pingfan Tang:
Sketched MinDist. CoRR abs/1907.02171 (2019) - [i49]Sunipa Dev, Tao Li, Jeff M. Phillips, Vivek Srikumar:
On Measuring and Mitigating Biased Inferences of Word Embeddings. CoRR abs/1908.09369 (2019) - [i48]Jasper C. H. Lee, Jerry Li, Christopher Musco, Jeff M. Phillips, Wai Ming Tai:
Finding the Mode of a Kernel Density Estimate. CoRR abs/1912.07673 (2019) - 2018
- [c53]Kevin Buchin
, Jeff M. Phillips, Pingfan Tang:
Approximating the Distribution of the Median and other Robust Estimators on Uncertain Data. SoCG 2018: 16:1-16:14 - [c52]Jeff M. Phillips, Wai Ming Tai:
Near-Optimal Coresets of Kernel Density Estimates. SoCG 2018: 66:1-66:13 - [c51]Michael Matheny, Jeff M. Phillips:
Practical Low-Dimensional Halfspace Range Space Sampling. ESA 2018: 62:1-62:14 - [c50]Aria Rezaei, Jie Gao, Jeff M. Phillips, Csaba D. Tóth:
Improved bounds on information dissemination by Manhattan Random Waypoint model. SIGSPATIAL/GIS 2018: 139-148 - [c49]Michael Matheny, Jeff M. Phillips:
Computing Approximate Statistical Discrepancy. ISAAC 2018: 32:1-32:13 - [c48]Yang Gao, Jeff M. Phillips, Yan Zheng, Renqiang Min, P. Thomas Fletcher, Guido Gerig
:
Fully convolutional structured LSTM networks for joint 4D medical image segmentation. ISBI 2018: 1104-1108 - [c47]Jeff M. Phillips, Wai Ming Tai:
Improved Coresets for Kernel Density Estimates. SODA 2018: 2718-2727 - [i47]Jeff M. Phillips, Wai Ming Tai:
Near-Optimal Coresets of Kernel Density Estimates. CoRR abs/1802.01751 (2018) - [i46]Jeff M. Phillips, Pingfan Tang:
A Data-Dependent Distance for Regression. CoRR abs/1804.11284 (2018) - [i45]Michael Matheny, Jeff M. Phillips:
Computing Approximate Statistical Discrepancy. CoRR abs/1804.11287 (2018) - [i44]Michael Matheny, Jeff M. Phillips:
Practical Low-Dimensional Halfspace Range Space Sampling. CoRR abs/1804.11307 (2018) - [i43]Sunipa Dev, Safia Hassan, Jeff M. Phillips:
Absolute Orientation for Word Embedding Alignment. CoRR abs/1806.01330 (2018) - [i42]Aria Rezaei, Jie Gao, Jeff M. Phillips, Csaba D. Tóth:
Improved Bounds on Information Dissemination by Manhattan Random Waypoint Model. CoRR abs/1809.07392 (2018) - [i41]Jeff M. Phillips, Wai Ming Tai:
Relative Error RKHS Embeddings for Gaussian Kernels. CoRR abs/1811.04136 (2018) - 2017
- [j11]Dong Xie
, Feifei Li, Jeff M. Phillips:
Distributed Trajectory Similarity Search. Proc. VLDB Endow. 10(11): 1478-1489 (2017) - [j10]Ran Wei, Daoqin Tong, Jeff M. Phillips:
An integrated classification scheme for mapping estimates and errors of estimation from the American Community Survey. Comput. Environ. Urban Syst. 63: 95-103 (2017) - [c46]Di Chen, Jeff M. Phillips:
Relative Error Embeddings of the Gaussian Kernel Distance. ALT 2017: 560-576 - [c45]Yan Zheng, Jeff M. Phillips:
Coresets for Kernel Regression. KDD 2017: 645-654 - [i40]Yan Zheng, Jeff M. Phillips:
Coresets for Kernel Regression. CoRR abs/1702.03644 (2017) - [i39]Yan Zheng, Yi Ou, Alexander Lex, Jeff M. Phillips:
Visualization of Big Spatial Data using Coresets for Kernel Density Estimates. CoRR abs/1709.04453 (2017) - [i38]Jeff M. Phillips, Wai Ming Tai:
Improved Coresets for Kernel Density Estimates. CoRR abs/1710.04325 (2017) - [i37]Tim Sodergren, Jessica Hair, Jeff M. Phillips, Bei Wang:
Visualizing Sensor Network Coverage with Location Uncertainty. CoRR abs/1710.06925 (2017) - 2016
- [j9]Jeff M. Phillips, Elad Verbin, Qin Zhang:
Lower Bounds for Number-in-Hand Multiparty Communication Complexity, Made Easy. SIAM J. Comput. 45(1): 174-196 (2016) - [j8]Mina Ghashami, Edo Liberty, Jeff M. Phillips, David P. Woodruff:
Frequent Directions: Simple and Deterministic Matrix Sketching. SIAM J. Comput. 45(5): 1762-1792 (2016) - [j7]Pankaj K. Agarwal, Boris Aronov
, Sariel Har-Peled
, Jeff M. Phillips, Ke Yi, Wuzhou Zhang:
Nearest-Neighbor Searching Under Uncertainty II. ACM Trans. Algorithms 13(1): 3:1-3:25 (2016) - [j6]Amey Desai, Mina Ghashami, Jeff M. Phillips:
Improved Practical Matrix Sketching with Guarantees. IEEE Trans. Knowl. Data Eng. 28(7): 1678-1690 (2016) - [j5]Jian Pei, Leman Akoglu, Hongrae Lee, Justin J. Levandoski, Xuelong Li, Rosa Meo, Carlos Ordonez, Jeff M. Phillips, Barbara Poblete, K. Selçuk Candan, Meng Wang, Ji-Rong Wen, Li Xiong, Wenjie Zhang:
EIC Editorial. IEEE Trans. Knowl. Data Eng. 28(10): 2535-2537 (2016) - [c44]Mina Ghashami, Daniel J. Perry, Jeff M. Phillips:
Streaming Kernel Principal Component Analysis. AISTATS 2016: 1365-1374 - [c43]Lingxiao Huang
, Jian Li, Jeff M. Phillips, Haitao Wang:
epsilon-Kernel Coresets for Stochastic Points. ESA 2016: 50:1-50:18 - [c42]Michael Matheny, Raghvendra Singh, Liang Zhang, Kaiqiang Wang, Jeff M. Phillips:
Scalable spatial scan statistics through sampling. SIGSPATIAL/GIS 2016: 20:1-20:10 - [c41]Mina Ghashami, Edo Liberty, Jeff M. Phillips:
Efficient Frequent Directions Algorithm for Sparse Matrices. KDD 2016: 845-854 - [c40]Pingfan Tang, Jeff M. Phillips:
The Robustness of Estimator Composition. NIPS 2016: 929-937 - [i36]Jeff M. Phillips:
Coresets and Sketches. CoRR abs/1601.00617 (2016) - [i35]Jeff M. Phillips, Pingfan Tang:
Approximate Distribution of L1 Median on Uncertain Data. CoRR abs/1601.00630 (2016) - [i34]Mina Ghashami, Edo Liberty, Jeff M. Phillips:
Efficient Frequent Directions Algorithm for Sparse Matrices. CoRR abs/1602.00412 (2016) - [i33]Di Chen, Jeff M. Phillips:
Relative Error Embeddings for the Gaussian Kernel Distance. CoRR abs/1602.05350 (2016) - [i32]Pankaj K. Agarwal, Boris Aronov, Sariel Har-Peled
, Jeff M. Phillips, Ke Yi, Wuzhou Zhang:
Nearest-Neighbor Searching Under Uncertainty II. CoRR abs/1606.00112 (2016) - [i31]Pingfan Tang, Jeff M. Phillips:
The Robustness of Estimator Composition. CoRR abs/1609.01226 (2016) - 2015
- [c39]Jeff M. Phillips, Yan Zheng:
Subsampling in Smoothed Range Spaces. ALT 2015: 224-238 - [c38]Jeff M. Phillips, Bei Wang, Yan Zheng:
Geometric Inference on Kernel Density Estimates. SoCG 2015: 857-871 - [c37]Yan Zheng, Jeff M. Phillips:
L∞ Error and Bandwidth Selection for Kernel Density Estimates of Large Data. KDD 2015: 1533-1542 - [i30]Mina Ghashami, Edo Liberty, Jeff M. Phillips, David P. Woodruff:
Frequent Directions : Simple and Deterministic Matrix Sketching. CoRR abs/1501.01711 (2015) - [i29]Amey Desai, Mina Ghashami, Jeff M. Phillips:
Improved Practical Matrix Sketching with Guarantees. CoRR abs/1501.06561 (2015) - [i28]Jeff M. Phillips, Yan Zheng:
Subsampling in Smoothed Range Spaces. CoRR abs/1510.09123 (2015) - [i27]Mina Ghashami, Daniel J. Perry, Jeff M. Phillips:
Streaming Kernel Principal Component Analysis. CoRR abs/1512.05059 (2015) - 2014
- [j4]Mina Ghashami, Jeff M. Phillips, Feifei Li:
Continuous Matrix Approximation on Distributed Data. Proc. VLDB Endow. 7(10): 809-820 (2014) - [c36]Mina Ghashami, Amey Desai, Jeff M. Phillips:
Improved Practical Matrix Sketching with Guarantees. ESA 2014: 467-479 - [c35]Mina Ghashami, Jeff M. Phillips:
Relative Errors for Deterministic Low-Rank Matrix Approximations. SODA 2014: 707-717 - [i26]Mina Ghashami, Jeff M. Phillips, Feifei Li:
Continuous Matrix Approximation on Distributed Data. CoRR abs/1404.7571 (2014) - [i25]Jian Li, Jeff M. Phillips, Haitao Wang:
$ε$-Kernel Coresets for Stochastic Points. CoRR abs/1411.0194 (2014) - 2013
- [j3]Peyman Afshani, Pankaj K. Agarwal, Lars Arge, Kasper Green Larsen, Jeff M. Phillips:
(Approximate) Uncertain Skylines. Theory Comput. Syst. 52(3): 342-366 (2013) - [j2]Pankaj K. Agarwal, Graham Cormode
, Zengfeng Huang
, Jeff M. Phillips, Zhewei Wei, Ke Yi:
Mergeable summaries. ACM Trans. Database Syst. 38(4): 26 (2013) - [c34]Amirali Abdullah, Samira Daruki, Jeff M. Phillips:
Range counting coresets for uncertain data. SoCG 2013: 223-232 - [c33]Yang Zhao, Neal Patwari, Jeff M. Phillips, Suresh Venkatasubramanian
:
Radio tomographic imaging and tracking of stationary and moving people via kernel distance. IPSN 2013: 229-240 - [c32]Pankaj K. Agarwal, Boris Aronov
, Sariel Har-Peled, Jeff M. Phillips, Ke Yi, Wuzhou Zhang:
Nearest neighbor searching under uncertainty II. PODS 2013: 115-126 - [c31]Yan Zheng, Jeffrey Jestes, Jeff M. Phillips, Feifei Li:
Quality and efficiency for kernel density estimates in large data. SIGMOD Conference 2013: 433-444 - [c30]