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ORCIDJeff M. Phillips
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- 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]