Simulated Knot Tying. - Jeff M. Phillips; Andrew M. Ladd; Lydia E. Kavraki (ICRA, 2002)

Guided Expansive Spaces Trees: a Search Strategy for Motion- and Cost-constrained State Spaces. - Jeff M. Phillips; Nazareth Bedrossian; Lydia E. Kavraki (ICRA, 2004)

On Bipartite Matching under the RMS Distance. - Jeff M. Phillips; Pankaj K. Agarwal (CCCG, 2006)

Spatial scan statistics: approximations and performance study. - Deepak Agarwal; Andrew McGregor 001; Jeff M. Phillips; Suresh Venkatasubramanian; Zhengyuan Zhu (KDD, 2006)

The hunting of the bump: on maximizing statistical discrepancy. - Deepak Agarwal; Jeff M. Phillips; Suresh Venkatasubramanian (SODA, 2006)

Segmenting Motifs in Protein-Protein Interface Surfaces. - Jeff M. Phillips; Johannes Rudolph; Pankaj K. Agarwal (WABI, 2006)

Outlier Robust ICP for Minimizing Fractional RMSD. - Jeff M. Phillips; Ran Liu; Carlo Tomasi (3DIM, 2007)

Value-Based Notification Conditions in Large-Scale Publish/Subscribe Systems. - Badrish Chandramouli; Jeff M. Phillips; Jun Yang 001 (VLDB, 2007)

An Efficient Algorithm for 2D Euclidean 2-Center with Outliers. - Pankaj K. Agarwal; Jeff M. Phillips (ESA, 2008)

Algorithms for epsilon-Approximations of Terrains. - Jeff M. Phillips (ICALP (1), 2008)

Spatial Scan Statistics for Graph Clustering. - Bei Wang 001; Jeff M. Phillips; Robert Schreiber; Dennis M. Wilkinson (SDM, 2008)

Algorithms for eps-approximations of Terrains - Jeff M. Phillips (CoRR, 2008)

Shape Fitting on Point Sets with Probability Distributions. - Maarten Löffler; Jeff M. Phillips (ESA, 2009)

Computing Hulls And Centerpoints In Positive Definite Space - P. Thomas Fletcher; John Moeller; Jeff M. Phillips; Suresh Venkatasubramanian (CoRR, 2009)

Stability of epsilon-Kernels. - Pankaj K. Agarwal; Jeff M. Phillips; Hai Yu 005 (ESA (1), 2010)

Universal multi-dimensional scaling. - Arvind Agarwal; Jeff M. Phillips; Suresh Venkatasubramanian (KDD, 2010)

Lipschitz Unimodal and Isotonic Regression on Paths and Trees. - Pankaj K. Agarwal; Jeff M. Phillips; Bardia Sadri (LATIN, 2010)

Metrics for Uncertainty Analysis and Visualization of Diffusion Tensor Images. - Fangxiang Jiao; Jeff M. Phillips; Jeroen G. Stinstra; Jens Krger; Raj Varma Kommaraju; Edward W. Hsu; Julie R. Korenberg; Chris R. Johnson 001 (MIAR, 2010)

Matching Shapes Using the Current Distance - Sarang C. Joshi; Raj Varma Kommaraju; Jeff M. Phillips; Suresh Venkatasubramanian (CoRR, 2010)

A Unified Algorithmic Framework for Multi-Dimensional Scaling - Arvind Agarwal; Jeff M. Phillips; Suresh Venkatasubramanian (CoRR, 2010)

Stability of epsilon-Kernels - Pankaj K. Agarwal; Jeff M. Phillips; Hai Yu 005 (CoRR, 2010)

Comparing distributions and shapes using the kernel distance. - Sarang C. Joshi; Raj Varma Kommaraju; Jeff M. Phillips; Suresh Venkatasubramanian (SCG, 2011)

Generating a Diverse Set of High-Quality Clusterings. - Jeff M. Phillips; Parasaran Raman; Suresh Venkatasubramanian (MultiClust@ECML/PKDD, 2011)

Spatially-Aware Comparison and Consensus for Clusterings. - Parasaran Raman; Jeff M. Phillips; Suresh Venkatasubramanian (SDM, 2011)

Horoball Hulls and Extents in Positive Definite Space. - P. Thomas Fletcher; John Moeller; Jeff M. Phillips; Suresh Venkatasubramanian (WADS, 2011)

Geometric Computations on Indecisive Points. - Allan Jørgensen; Maarten Löffler; Jeff M. Phillips (WADS, 2011)

A Gentle Introduction to the Kernel Distance - Jeff M. Phillips; Suresh Venkatasubramanian (CoRR, 2011)

ε-Samples of Kernels - Jeff M. Phillips (CoRR, 2011)

Efficient Protocols for Distributed Classification and Optimization. - Hal Daumé III; Jeff M. Phillips; Avishek Saha; Suresh Venkatasubramanian (ALT, 2012)

Uncertainty visualization in HARDI based on ensembles of ODFs. - Fangxiang Jiao; Jeff M. Phillips; Yaniv Gur; Chris R. Johnson 001 (PacificVis, 2012)

Efficient Threshold Monitoring for Distributed Probabilistic Data. - Mingwang Tang; Feifei Li 001; Jeff M. Phillips; Jeffrey Jestes (ICDE, 2012)

Sensor Network Localization for Moving Sensors. - Arvind Agarwal; Hal Daumé III; Jeff M. Phillips; Suresh Venkatasubramanian (ICDM Workshops, 2012)

Geometric Computations on Indecisive and Uncertain Points - Allan Jørgensen; Maarten Löffler; Jeff M. Phillips (CoRR, 2012)

Chernoff-Hoeffding Inequality and Applications - Jeff M. Phillips (CoRR, 2012)

Protocols for Learning Classifiers on Distributed Data. - Hal Daumé III; Jeff M. Phillips; Avishek Saha; Suresh Venkatasubramanian (AISTATS, 2012)

Ranking Large Temporal Data. - Jeffrey Jestes; Jeff M. Phillips; Feifei Li 001; Mingwang Tang (Proc. VLDB Endow., 2012)

Range counting coresets for uncertain data. - Amirali Abdullah; Samira Daruki; Jeff M. Phillips (SoCG, 2013)

Radio tomographic imaging and tracking of stationary and moving people via kernel distance. - Yang Zhao 020; Neal Patwari; Jeff M. Phillips; Suresh Venkatasubramanian (IPSN, 2013)

Quality and efficiency for kernel density estimates in large data. - Yan Zheng 001; Jeffrey Jestes; Jeff M. Phillips; Feifei Li 001 (SIGMOD Conference, 2013)

Є-Samples for Kernels. - Jeff M. Phillips (SODA, 2013)

Rethinking Abstractions for Big Data: Why, Where, How, and What. - Mary W. Hall; Robert M. Kirby; Feifei Li 001; Miriah D. Meyer; Valerio Pascucci; Jeff M. Phillips; Robert Ricci; Jacobus E. van der Merwe; Suresh Venkatasubramanian (CoRR, 2013)

(Approximate) Uncertain Skylines. - Peyman Afshani; Pankaj K. Agarwal; Lars Arge; Kasper Green Larsen; Jeff M. Phillips (Theory Comput. Syst., 2013)

Mergeable summaries. - Pankaj K. Agarwal; Graham Cormode; Zengfeng Huang; Jeff M. Phillips; Zhewei Wei; Ke Yi 001 (ACM Trans. Database Syst., 2013)

Relative Errors for Deterministic Low-Rank Matrix Approximations. - Mina Ghashami; Jeff M. Phillips (SODA, 2014)

$ε$-Kernel Coresets for Stochastic Points. - Jian Li 015; Jeff M. Phillips; Haitao Wang 001 (CoRR, 2014)

Continuous Matrix Approximation on Distributed Data. - Mina Ghashami; Jeff M. Phillips; Feifei Li 001 (Proc. VLDB Endow., 2014)

Subsampling in Smoothed Range Spaces. - Jeff M. Phillips; Yan Zheng 001 (ALT, 2015)

Geometric Inference on Kernel Density Estimates. - Jeff M. Phillips; Bei Wang 001; Yan Zheng 001 (SoCG, 2015)

L∞ Error and Bandwidth Selection for Kernel Density Estimates of Large Data. - Yan Zheng 001; Jeff M. Phillips (KDD, 2015)

Streaming Kernel Principal Component Analysis. - Mina Ghashami; Daniel J. Perry; Jeff M. Phillips (AISTATS, 2016)

epsilon-Kernel Coresets for Stochastic Points. - Lingxiao Huang; Jian Li 015; Jeff M. Phillips; Haitao Wang 001 (ESA, 2016)

Scalable spatial scan statistics through sampling. - Michael Matheny; Raghvendra Singh; Liang Zhang; Kaiqiang Wang; Jeff M. Phillips (SIGSPATIAL/GIS, 2016)

Efficient Frequent Directions Algorithm for Sparse Matrices. - Mina Ghashami; Edo Liberty; Jeff M. Phillips (KDD, 2016)

The Robustness of Estimator Composition. - Pingfan Tang; Jeff M. Phillips (NIPS, 2016)

Coresets and Sketches. - Jeff M. Phillips (CoRR, 2016)

Approximate Distribution of L1 Median on Uncertain Data. - Jeff M. Phillips; Pingfan Tang (CoRR, 2016)

Frequent Directions: Simple and Deterministic Matrix Sketching. - Mina Ghashami; Edo Liberty; Jeff M. Phillips; David P. Woodruff (SIAM J. Comput., 2016)

Lower Bounds for Number-in-Hand Multiparty Communication Complexity, Made Easy. - Jeff M. Phillips; Elad Verbin; Qin Zhang 001 (SIAM J. Comput., 2016)

Nearest-Neighbor Searching Under Uncertainty II. - Pankaj K. Agarwal; Boris Aronov; Sariel Har-Peled; Jeff M. Phillips; Ke Yi 001; Wuzhou Zhang (ACM Trans. Algorithms, 2016)

Improved Practical Matrix Sketching with Guarantees. - Amey Desai; Mina Ghashami; Jeff M. Phillips (IEEE Trans. Knowl. Data Eng., 2016)

EIC Editorial. - Jian Pei 001; Leman Akoglu; Hongrae Lee; Justin J. Levandoski; Xuelong Li 001; Rosa Meo; Carlos Ordonez 001; Jeff M. Phillips; Barbara Poblete; K. Selçuk Candan; Meng Wang 001; Ji-Rong Wen; et al. (IEEE Trans. Knowl. Data Eng., 2016)

Relative Error Embeddings of the Gaussian Kernel Distance. - Di Chen; Jeff M. Phillips (ALT, 2017)

Coresets for Kernel Regression. - Yan Zheng 001; Jeff M. Phillips (KDD, 2017)

Visualizing Sensor Network Coverage with Location Uncertainty. - Tim Sodergren; Jessica Hair; Jeff M. Phillips; Bei Wang 001 (CoRR, 2017)

Distributed Trajectory Similarity Search. - Dong Xie 001; Feifei Li 001; Jeff M. Phillips (Proc. VLDB Endow., 2017)

An integrated classification scheme for mapping estimates and errors of estimation from the American Community Survey. - Ran Wei; Daoqin Tong; Jeff M. Phillips (Comput. Environ. Urban Syst., 2017)

Approximating the Distribution of the Median and other Robust Estimators on Uncertain Data. - Kevin Buchin; Jeff M. Phillips; Pingfan Tang (SoCG, 2018)

Practical Low-Dimensional Halfspace Range Space Sampling. - Michael Matheny; Jeff M. Phillips (ESA, 2018)

Improved bounds on information dissemination by Manhattan Random Waypoint model. - Aria Rezaei; Jie Gao 001; Jeff M. Phillips; Csaba D. Tóth (SIGSPATIAL/GIS, 2018)

Computing Approximate Statistical Discrepancy. - Michael Matheny; Jeff M. Phillips (ISAAC, 2018)

Fully convolutional structured LSTM networks for joint 4D medical image segmentation. - Yang Gao 031; Jeff M. Phillips; Yan Zheng 001; Renqiang Min; P. Thomas Fletcher; Guido Gerig (ISBI, 2018)

Improved Coresets for Kernel Density Estimates. - Jeff M. Phillips; Wai Ming Tai (SODA, 2018)

A Data-Dependent Distance for Regression. - Jeff M. Phillips; Pingfan Tang (CoRR, 2018)

Absolute Orientation for Word Embedding Alignment. - Sunipa Dev; Safia Hassan; Jeff M. Phillips (CoRR, 2018)

Relative Error RKHS Embeddings for Gaussian Kernels. - Jeff M. Phillips; Wai Ming Tai (CoRR, 2018)

Attenuating Bias in Word vectors. - Sunipa Dev; Jeff M. Phillips (AISTATS, 2019)

Independent Range Sampling, Revisited Again. - Peyman Afshani; Jeff M. Phillips (SoCG, 2019)

The VC Dimension of Metric Balls Under Fréchet and Hausdorff Distances. - Anne Driemel; Jeff M. Phillips; Ioannis Psarros (SoCG, 2019)

The Kernel Spatial Scan Statistic. - Mingxuan Han; Michael Matheny; Jeff M. Phillips (SIGSPATIAL/GIS, 2019)

Simple Distances for Trajectories via Landmarks. - Jeff M. Phillips; Pingfan Tang (SIGSPATIAL/GIS, 2019)

Learning In Practice: Reasoning About Quantization. - Annie Cherkaev; Waiming Tai; Jeff M. Phillips; Vivek Srikumar (CoRR, 2019)

Finding the Mode of a Kernel Density Estimate. - Jasper C. H. Lee; Jerry Li 001; Christopher Musco; Jeff M. Phillips; Wai Ming Tai (CoRR, 2019)

On Measuring and Mitigating Biased Inferences of Word Embeddings. - Sunipa Dev; Tao Li 039; Jeff M. Phillips; Vivek Srikumar (AAAI, 2020)

The GaussianSketch for Almost Relative Error Kernel Distance. - Jeff M. Phillips; Wai Ming Tai (APPROX-RANDOM, 2020)

Sketched MinDist. - Jeff M. Phillips; Pingfan Tang (SoCG, 2020)

Near-Optimal Coresets of Kernel Density Estimates. - Jeff M. Phillips; Wai Ming Tai (Discret. Comput. Geom., 2020)

Scalable Spatial Scan Statistics for Trajectories. - Michael Matheny; Dong Xie 001; Jeff M. Phillips (ACM Trans. Knowl. Discov. Data, 2020)

A Deterministic Streaming Sketch for Ridge Regression. - Benwei Shi; Jeff M. Phillips (AISTATS, 2021)

OSCaR: Orthogonal Subspace Correction and Rectification of Biases in Word Embeddings. - Sunipa Dev; Tao Li 039; Jeff M. Phillips; Vivek Srikumar (EMNLP (1), 2021)

Harms of Gender Exclusivity and Challenges in Non-Binary Representation in Language Technologies. - Sunipa Dev; Masoud Monajatipoor; Anaelia Ovalle; Arjun Subramonian; Jeff M. Phillips; Kai-Wei Chang (EMNLP (1), 2021)

Finding an Approximate Mode of a Kernel Density Estimate. - Jasper C. H. Lee; Jerry Li 001; Christopher Musco; Jeff M. Phillips; Wai Ming Tai (ESA, 2021)

Constrained Non-Affine Alignment of Embeddings. - Yuwei Wang; Yan Zheng 001; Yanqing Peng; Chin-Chia Michael Yeh; Zhongfang Zhuang; Mahashweta Das; Mangesh Bendre; Feifei Li 001; Wei Zhang 189; Jeff M. Phillips (ICDM, 2021)

Approximate Maximum Halfspace Discrepancy. - Michael Matheny; Jeff M. Phillips (ISAAC, 2021)

A Visual Tour of Bias Mitigation Techniques for Word Representations. - Archit Rathore; Sunipa Dev; Jeff M. Phillips; Vivek Srikumar; Bei Wang 001 (KDD, 2021)

Orientation-Preserving Vectorized Distance Between Curves. - Jeff M. Phillips; Hasan Pourmahmood Aghababa (MSML, 2021)

Self-Adaptable Point Processes with Nonparametric Time Decays. - Zhimeng Pan; Zheng Wang 042; Jeff M. Phillips; Shandian Zhe (NeurIPS, 2021)

An Interactive Visual Demo of Bias Mitigation Techniques for Word Representations From a Geometric Perspective. - Archit Rathore; Sunipa Dev; Vivek Srikumar; Jeff M. Phillips; Yan Zheng 001; Chin-Chia Michael Yeh; Junpeng Wang 001; Wei Zhang 189; Bei Wang 001 (NeurIPS (Competition and Demos), 2021)

Spatial Independent Range Sampling. - Dong Xie 001; Jeff M. Phillips; Michael Matheny; Feifei Li 001 (SIGMOD Conference, 2021)

At-the-time and Back-in-time Persistent Sketches. - Benwei Shi; Zhuoyue Zhao 001; Yanqing Peng; Feifei Li 001; Jeff M. Phillips (SIGMOD Conference, 2021)

VERB: Visualizing and Interpreting Bias Mitigation Techniques for Word Representations. - Archit Rathore; Sunipa Dev; Jeff M. Phillips; Vivek Srikumar; Yan Zheng 001; Chin-Chia Michael Yeh; Junpeng Wang 001; Wei Zhang 189; Bei Wang 001 (CoRR, 2021)

Hiding Signal Strength Interference from Outside Adversaries. - Mingxuan Han; Jeff M. Phillips; Sneha Kumar Kasera (CoRR, 2021)

Computational Geometry (Dagstuhl Seminar 21181). - Siu-Wing Cheng; Anne Driemel; Jeff M. Phillips (Dagstuhl Reports, 2021)

The VC Dimension of Metric Balls under Fréchet and Hausdorff Distances. - Anne Driemel; André Nusser; Jeff M. Phillips; Ioannis Psarros (Discret. Comput. Geom., 2021)

Predicting intent behind selections in scatterplot visualizations. - Kiran Gadhave; Jochen Görtler; Zach Cutler; Carolina Nobre; Oliver Deussen; Miriah Meyer; Jeff M. Phillips; Alexander Lex (Inf. Vis., 2021)

Closed form word embedding alignment. - Sunipa Dev; Safia Hassan; Jeff M. Phillips (Knowl. Inf. Syst., 2021)

Visualization of Big Spatial Data Using Coresets for Kernel Density Estimates. - Yan Zheng 001; Yi Ou; Alexander Lex; Jeff M. Phillips (IEEE Trans. Big Data, 2021)

Inferencing hourly traffic volume using data-driven machine learning and graph theory. - Zhiyan Yi; Xiaoyue Cathy Liu; Nikola Markovic; Jeff M. Phillips (Comput. Environ. Urban Syst., 2021)

Semantic embedding for regions of interest. - Debjyoti Paul; Feifei Li 001; Jeff M. Phillips (VLDB J., 2021)

Quantized Wasserstein Procrustes Alignment of Word Embedding Spaces. - Prince Osei Aboagye; Yan Zheng 001; Chin-Chia Michael Yeh; Junpeng Wang 001; Zhongfang Zhuang; Huiyuan Chen; Liang Wang 047; Wei Zhang 189; Jeff M. Phillips (AMTA, 2022)

Using Existential Theory of the Reals to Bound VC Dimension. - Austin Watkins; Jeff M. Phillips (CCCG, 2022)

Efficient and Oblivious Query Processing for Range and kNN Queries (Extended Abstract). - Zhao Chang; Dong Xie 001; Feifei Li 001; Jeff M. Phillips; Rajeev Balasubramonian (ICDE, 2022)

Normalization of Language Embeddings for Cross-Lingual Alignment. - Prince Osei Aboagye; Yan Zheng 001; Chin-Chia Michael Yeh; Junpeng Wang 001; Wei Zhang 189; Liang Wang 047; Hao Yang 007; Jeff M. Phillips (ICLR, 2022)

Batch Multi-Fidelity Active Learning with Budget Constraints. - Shibo Li; Jeff M. Phillips; Xin Yu 003; Robert M. Kirby; Shandian Zhe (NeurIPS, 2022)

Practical and configurable network traffic classification using probabilistic machine learning. - Jiahui Chen 007; Joe Breen; Jeff M. Phillips; Jacobus E. van der Merwe (Clust. Comput., 2022)

Classifying Spatial Trajectories. - Hasan Pourmahmood Aghababa; Jeff M. Phillips (CoRR, 2022)

Efficient Oblivious Query Processing for Range and kNN Queries. - Zhao Chang; Dong Xie 001; Feifei Li 001; Jeff M. Phillips; Rajeev Balasubramonian (IEEE Trans. Knowl. Data Eng., 2022)

Local Kernel Ridge Regression for Scalable, Interpolating, Continuous Regression. - Mingxuan Han; Chenglong Ye; Jeff M. Phillips (Trans. Mach. Learn. Res., 2022)

Sketching Multidimensional Time Series for Fast Discord Mining. - Chin-Chia Michael Yeh; Yan Zheng 001; Menghai Pan; Huiyuan Chen; Zhongfang Zhuang; Junpeng Wang 001; Liang Wang 047; Wei Zhang 189; Jeff M. Phillips; Eamonn J. Keogh (IEEE Big Data, 2023)

An Efficient Content-based Time Series Retrieval System. - Chin-Chia Michael Yeh; Huiyuan Chen; Xin Dai; Yan Zheng 001; Junpeng Wang 001; Vivian Lai; Yujie Fan; Audrey Der; Zhongfang Zhuang; Liang Wang 047; Wei Zhang 189; Jeff M. Phillips (CIKM, 2023)

Interpretable Debiasing of Vectorized Language Representations with Iterative Orthogonalization. - Prince Osei Aboagye; Yan Zheng 001; Jack Shunn; Chin-Chia Michael Yeh; Junpeng Wang 001; Zhongfang Zhuang; Huiyuan Chen; Liang Wang 047; Wei Zhang 189; Jeff M. Phillips (ICLR, 2023)

An NSF REU Site Based on Trust and Reproducibility of Intelligent Computation: Experience Report. - Mary W. Hall; Ganesh Gopalakrishnan; Eric Eide; Johanna Cohoon; Jeff M. Phillips; Mu Zhang 001; Shireen Y. Elhabian; Aditya Bhaskara; Harvey Dam; Artem Yadrov; Tushar Kataria; Amir Mohammad Tavakkoli; et al. (SC Workshops, 2023)

For Kernel Range Spaces a Constant Number of Queries Are Sufficient. - Jeff M. Phillips; Hasan Pourmahmood Aghababa (CoRR, 2023)

Locally Adaptive and Differentiable Regression. - Mingxuan Han; Varun Shankar; Jeff M. Phillips; Chenglong Ye (CoRR, 2023)

On Mergable Coresets for Polytope Distance. - Benwei Shi; Aditya Bhaskara; Wai Ming Tai; Jeff M. Phillips (CoRR, 2023)

Computational Geometry (Dagstuhl Seminar 23221). - Siu-Wing Cheng; Maarten Löffler; Jeff M. Phillips; Aleksandr Popov 001 (Dagstuhl Reports, 2023)

Computational Geometry of Earth System Analysis (Dagstuhl Seminar 23342). - Susanne Crewell; Anne Driemel; Jeff M. Phillips; Dwaipayan Chatterjee (Dagstuhl Reports, 2023)

An experimental study on classifying spatial trajectories. - Hasan Pourmahmood Aghababa; Jeff M. Phillips (Knowl. Inf. Syst., 2023)

Ferret: Reviewing Tabular Datasets for Manipulation. - Devin Lange; Shaurya Sahai; Jeff M. Phillips; Alexander Lex (Comput. Graph. Forum, 2023)

No Dimensional Sampling Coresets for Classification. - Meysam Alishahi; Jeff M. Phillips (ICML, 2024)

Mitigating Exploitation Bias in Learning to Rank with an Uncertainty-aware Empirical Bayes Approach. - Tao Yang 030; Cuize Han; Chen Luo 003; Parth Gupta; Jeff M. Phillips; Qingyao Ai (WWW, 2024)

Linear Distance Metric Learning with Noisy Labels. - Meysam Alishahi; Anna Little; Jeff M. Phillips (J. Mach. Learn. Res., 2024)

VERB: Visualizing and Interpreting Bias Mitigation Techniques Geometrically for Word Representations. - Archit Rathore; Sunipa Dev; Jeff M. Phillips; Vivek Srikumar; Yan Zheng 001; Chin-Chia Michael Yeh; Junpeng Wang 001; Wei Zhang 189; Bei Wang 001 (ACM Trans. Interact. Intell. Syst., 2024)

Estimation of Large Zipfian Distributions with Sort and Snap. - Peter Matthew Jacobs; Anirban Bhattacharya; Debdeep Pati; Lekha Patel; Jeff M. Phillips (AISTATS, 2025)

Standard Gaussian Process is All You Need for High-Dimensional Bayesian Optimization. - Zhitong Xu; Haitao Wang 001; Jeff M. Phillips; Shandian Zhe (ICLR, 2025)

Robust High-Dimensional Mean Estimation With Low Data Size, an Empirical Study. - Cullen Anderson; Jeff M. Phillips (Trans. Mach. Learn. Res., 2025)

Fast Comparative Analysis of Merge Trees Using Locality Sensitive Hashing. - Weiran Lyu; Raghavendra Sridharamurthy; Jeff M. Phillips; Bei Wang 001 (IEEE Trans. Vis. Comput. Graph., 2025)

Efficient and Stable Multi-Dimensional Kolmogorov-Smirnov Distance. - Peter Matthew Jacobs; Foad Namjoo; Jeff M. Phillips (CoRR, 2025)

Trajectory Minimum Touching Ball. - Jeff M. Phillips; Jens Kristian Refsgaard Schou (CoRR, 2025)

Beyond Monoliths: Expert Orchestration for More Capable, Democratic, and Safe Large Language Models. - Philip Quirke; Narmeen Oozeer; Chaithanya Bandi; Amir Abdullah; Jason Hoelscher-Obermaier; Jeff M. Phillips; Joshua Greaves; Clement Neo; Fazl Barez; Shriyash Upadhyay (CoRR, 2025)

Zombie Hashing: Reanimating Tombstones in Graveyard. - Yuvaraj Chesetti; Benwei Shi; Jeff M. Phillips; Prashant Pandey 001 (Proc. ACM Manag. Data, 2025)