Jeff M. Phillips

Orcid: 0000-0003-1169-2965

Affiliations:
  • University of Utah, School of Computing
  • Duke University, Department of Computer Science


According to our database1, Jeff M. Phillips authored at least 133 papers between 2002 and 2025.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of two.

Timeline

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Bibliography

2025
Fast Comparative Analysis of Merge Trees Using Locality Sensitive Hashing.
IEEE Trans. Vis. Comput. Graph., January, 2025

2024
VERB: Visualizing and Interpreting Bias Mitigation Techniques Geometrically for Word Representations.
ACM Trans. Interact. Intell. Syst., March, 2024

Linear Distance Metric Learning with Noisy Labels.
J. Mach. Learn. Res., 2024

Mitigating Exploitation Bias in Learning to Rank with an Uncertainty-aware Empirical Bayes Approach.
Proceedings of the ACM on Web Conference 2024, 2024

No Dimensional Sampling Coresets for Classification.
Proceedings of the Forty-first International Conference on Machine Learning, 2024

2023
Ferret: Reviewing Tabular Datasets for Manipulation.
Comput. Graph. Forum, June, 2023

An experimental study on classifying spatial trajectories.
Knowl. Inf. Syst., April, 2023

Computational Geometry of Earth System Analysis (Dagstuhl Seminar 23342).
Dagstuhl Reports, 2023

Computational Geometry (Dagstuhl Seminar 23221).
Dagstuhl Reports, 2023

On Mergable Coresets for Polytope Distance.
CoRR, 2023

Locally Adaptive and Differentiable Regression.
CoRR, 2023

For Kernel Range Spaces a Constant Number of Queries Are Sufficient.
CoRR, 2023

An NSF REU Site Based on Trust and Reproducibility of Intelligent Computation: Experience Report.
Proceedings of the SC '23 Workshops of The International Conference on High Performance Computing, 2023

Interpretable Debiasing of Vectorized Language Representations with Iterative Orthogonalization.
Proceedings of the Eleventh International Conference on Learning Representations, 2023

An Efficient Content-based Time Series Retrieval System.
Proceedings of the 32nd ACM International Conference on Information and Knowledge Management, 2023

Sketching Multidimensional Time Series for Fast Discord Mining.
Proceedings of the IEEE International Conference on Big Data, 2023

2022
Local Kernel Ridge Regression for Scalable, Interpolating, Continuous Regression.
Trans. Mach. Learn. Res., 2022

Efficient Oblivious Query Processing for Range and kNN Queries.
IEEE Trans. Knowl. Data Eng., 2022

Classifying Spatial Trajectories.
CoRR, 2022

Practical and configurable network traffic classification using probabilistic machine learning.
Clust. Comput., 2022

Batch Multi-Fidelity Active Learning with Budget Constraints.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Normalization of Language Embeddings for Cross-Lingual Alignment.
Proceedings of the Tenth International Conference on Learning Representations, 2022

Efficient and Oblivious Query Processing for Range and kNN Queries (Extended Abstract).
Proceedings of the 38th IEEE International Conference on Data Engineering, 2022

Using Existential Theory of the Reals to Bound VC Dimension.
Proceedings of the 34th Canadian Conference on Computational Geometry, 2022

Quantized Wasserstein Procrustes Alignment of Word Embedding Spaces.
Proceedings of the 15th biennial conference of the Association for Machine Translation in the Americas (Volume 1: Research Track), 2022

2021
Semantic embedding for regions of interest.
VLDB J., 2021

Inferencing hourly traffic volume using data-driven machine learning and graph theory.
Comput. Environ. Urban Syst., 2021

Visualization of Big Spatial Data Using Coresets for Kernel Density Estimates.
IEEE Trans. Big Data, 2021

Closed form word embedding alignment.
Knowl. Inf. Syst., 2021

Predicting intent behind selections in scatterplot visualizations.
Inf. Vis., 2021

The VC Dimension of Metric Balls under Fréchet and Hausdorff Distances.
Discret. Comput. Geom., 2021

Computational Geometry (Dagstuhl Seminar 21181).
Dagstuhl Reports, 2021

Hiding Signal Strength Interference from Outside Adversaries.
CoRR, 2021

VERB: Visualizing and Interpreting Bias Mitigation Techniques for Word Representations.
CoRR, 2021

At-the-time and Back-in-time Persistent Sketches.
Proceedings of the SIGMOD '21: International Conference on Management of Data, 2021

Spatial Independent Range Sampling.
Proceedings of the SIGMOD '21: International Conference on Management of Data, 2021

An Interactive Visual Demo of Bias Mitigation Techniques for Word Representations From a Geometric Perspective.
Proceedings of the NeurIPS 2021 Competitions and Demonstrations Track, 2021

Self-Adaptable Point Processes with Nonparametric Time Decays.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Orientation-Preserving Vectorized Distance Between Curves.
Proceedings of the Mathematical and Scientific Machine Learning, 2021

A Visual Tour of Bias Mitigation Techniques for Word Representations.
Proceedings of the KDD '21: The 27th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2021

Approximate Maximum Halfspace Discrepancy.
Proceedings of the 32nd International Symposium on Algorithms and Computation, 2021

Constrained Non-Affine Alignment of Embeddings.
Proceedings of the IEEE International Conference on Data Mining, 2021

Finding an Approximate Mode of a Kernel Density Estimate.
Proceedings of the 29th Annual European Symposium on Algorithms, 2021

Harms of Gender Exclusivity and Challenges in Non-Binary Representation in Language Technologies.
Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing, 2021

OSCaR: Orthogonal Subspace Correction and Rectification of Biases in Word Embeddings.
Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing, 2021

A Deterministic Streaming Sketch for Ridge Regression.
Proceedings of the 24th International Conference on Artificial Intelligence and Statistics, 2021

2020
Scalable Spatial Scan Statistics for Trajectories.
ACM Trans. Knowl. Discov. Data, 2020

Near-Optimal Coresets of Kernel Density Estimates.
Discret. Comput. Geom., 2020

Sketched MinDist.
Proceedings of the 36th International Symposium on Computational Geometry, 2020

The GaussianSketch for Almost Relative Error Kernel Distance.
Proceedings of the Approximation, 2020

On Measuring and Mitigating Biased Inferences of Word Embeddings.
Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

2019
Finding the Mode of a Kernel Density Estimate.
CoRR, 2019

Learning In Practice: Reasoning About Quantization.
CoRR, 2019

Simple Distances for Trajectories via Landmarks.
Proceedings of the 27th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems, 2019

The Kernel Spatial Scan Statistic.
Proceedings of the 27th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems, 2019

The VC Dimension of Metric Balls Under Fréchet and Hausdorff Distances.
Proceedings of the 35th International Symposium on Computational Geometry, 2019

Independent Range Sampling, Revisited Again.
Proceedings of the 35th International Symposium on Computational Geometry, 2019

Attenuating Bias in Word vectors.
Proceedings of the 22nd International Conference on Artificial Intelligence and Statistics, 2019

2018
Relative Error RKHS Embeddings for Gaussian Kernels.
CoRR, 2018

Absolute Orientation for Word Embedding Alignment.
CoRR, 2018

A Data-Dependent Distance for Regression.
CoRR, 2018

Improved Coresets for Kernel Density Estimates.
Proceedings of the Twenty-Ninth Annual ACM-SIAM Symposium on Discrete Algorithms, 2018

Fully convolutional structured LSTM networks for joint 4D medical image segmentation.
Proceedings of the 15th IEEE International Symposium on Biomedical Imaging, 2018

Computing Approximate Statistical Discrepancy.
Proceedings of the 29th International Symposium on Algorithms and Computation, 2018

Improved bounds on information dissemination by Manhattan Random Waypoint model.
Proceedings of the 26th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems, 2018

Practical Low-Dimensional Halfspace Range Space Sampling.
Proceedings of the 26th Annual European Symposium on Algorithms, 2018

Approximating the Distribution of the Median and other Robust Estimators on Uncertain Data.
Proceedings of the 34th International Symposium on Computational Geometry, 2018

2017
An integrated classification scheme for mapping estimates and errors of estimation from the American Community Survey.
Comput. Environ. Urban Syst., 2017

Distributed Trajectory Similarity Search.
Proc. VLDB Endow., 2017

Visualizing Sensor Network Coverage with Location Uncertainty.
CoRR, 2017

Coresets for Kernel Regression.
Proceedings of the 23rd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, Halifax, NS, Canada, August 13, 2017

Relative Error Embeddings of the Gaussian Kernel Distance.
Proceedings of the International Conference on Algorithmic Learning Theory, 2017

2016
EIC Editorial.
IEEE Trans. Knowl. Data Eng., 2016

Improved Practical Matrix Sketching with Guarantees.
IEEE Trans. Knowl. Data Eng., 2016

Nearest-Neighbor Searching Under Uncertainty II.
ACM Trans. Algorithms, 2016

Lower Bounds for Number-in-Hand Multiparty Communication Complexity, Made Easy.
SIAM J. Comput., 2016

Frequent Directions: Simple and Deterministic Matrix Sketching.
SIAM J. Comput., 2016

Approximate Distribution of L1 Median on Uncertain Data.
CoRR, 2016

Coresets and Sketches.
CoRR, 2016

The Robustness of Estimator Composition.
Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

Efficient Frequent Directions Algorithm for Sparse Matrices.
Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2016

Scalable spatial scan statistics through sampling.
Proceedings of the 24th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems, GIS 2016, Burlingame, California, USA, October 31, 2016

epsilon-Kernel Coresets for Stochastic Points.
Proceedings of the 24th Annual European Symposium on Algorithms, 2016

Streaming Kernel Principal Component Analysis.
Proceedings of the 19th International Conference on Artificial Intelligence and Statistics, 2016

2015
L∞ Error and Bandwidth Selection for Kernel Density Estimates of Large Data.
Proceedings of the 21th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2015

Geometric Inference on Kernel Density Estimates.
Proceedings of the 31st International Symposium on Computational Geometry, 2015

Subsampling in Smoothed Range Spaces.
Proceedings of the Algorithmic Learning Theory - 26th International Conference, 2015

2014
Continuous Matrix Approximation on Distributed Data.
Proc. VLDB Endow., 2014

$ε$-Kernel Coresets for Stochastic Points.
CoRR, 2014

Relative Errors for Deterministic Low-Rank Matrix Approximations.
Proceedings of the Twenty-Fifth Annual ACM-SIAM Symposium on Discrete Algorithms, 2014

2013
Mergeable summaries.
ACM Trans. Database Syst., 2013

(Approximate) Uncertain Skylines.
Theory Comput. Syst., 2013

Rethinking Abstractions for Big Data: Why, Where, How, and What.
CoRR, 2013

Є-Samples for Kernels.
Proceedings of the Twenty-Fourth Annual ACM-SIAM Symposium on Discrete Algorithms, 2013

Quality and efficiency for kernel density estimates in large data.
Proceedings of the ACM SIGMOD International Conference on Management of Data, 2013

Radio tomographic imaging and tracking of stationary and moving people via kernel distance.
Proceedings of the 12th International Conference on Information Processing in Sensor Networks (co-located with CPS Week 2013), 2013

Range counting coresets for uncertain data.
Proceedings of the Symposium on Computational Geometry 2013, 2013

2012
Ranking Large Temporal Data.
Proc. VLDB Endow., 2012

Protocols for Learning Classifiers on Distributed Data.
Proceedings of the Fifteenth International Conference on Artificial Intelligence and Statistics, 2012

Chernoff-Hoeffding Inequality and Applications
CoRR, 2012

Geometric Computations on Indecisive and Uncertain Points
CoRR, 2012

Sensor Network Localization for Moving Sensors.
Proceedings of the 12th IEEE International Conference on Data Mining Workshops, 2012

Efficient Threshold Monitoring for Distributed Probabilistic Data.
Proceedings of the IEEE 28th International Conference on Data Engineering (ICDE 2012), 2012

Uncertainty visualization in HARDI based on ensembles of ODFs.
Proceedings of the 2012 IEEE Pacific Visualization Symposium, 2012

Efficient Protocols for Distributed Classification and Optimization.
Proceedings of the Algorithmic Learning Theory - 23rd International Conference, 2012

2011
ε-Samples of Kernels
CoRR, 2011

A Gentle Introduction to the Kernel Distance
CoRR, 2011

Geometric Computations on Indecisive Points.
Proceedings of the Algorithms and Data Structures - 12th International Symposium, 2011

Horoball Hulls and Extents in Positive Definite Space.
Proceedings of the Algorithms and Data Structures - 12th International Symposium, 2011

Spatially-Aware Comparison and Consensus for Clusterings.
Proceedings of the Eleventh SIAM International Conference on Data Mining, 2011

Generating a Diverse Set of High-Quality Clusterings.
Proceedings of the 2nd MultiClust Workshop: Discovering, 2011

Comparing distributions and shapes using the kernel distance.
Proceedings of the 27th ACM Symposium on Computational Geometry, 2011

2010
Stability of epsilon-Kernels
CoRR, 2010

A Unified Algorithmic Framework for Multi-Dimensional Scaling
CoRR, 2010

Matching Shapes Using the Current Distance
CoRR, 2010

Metrics for Uncertainty Analysis and Visualization of Diffusion Tensor Images.
Proceedings of the Medical Imaging and Augmented Reality - 5th International Workshop, 2010

Lipschitz Unimodal and Isotonic Regression on Paths and Trees.
Proceedings of the LATIN 2010: Theoretical Informatics, 2010

Universal multi-dimensional scaling.
Proceedings of the 16th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2010

Stability of <i>epsilon</i>-Kernels.
Proceedings of the Algorithms, 2010

2009
Computing Hulls And Centerpoints In Positive Definite Space
CoRR, 2009

Shape Fitting on Point Sets with Probability Distributions.
Proceedings of the Algorithms, 2009

2008
Algorithms for eps-approximations of Terrains
CoRR, 2008

Spatial Scan Statistics for Graph Clustering.
Proceedings of the SIAM International Conference on Data Mining, 2008

Algorithms for epsilon-Approximations of Terrains.
Proceedings of the Automata, Languages and Programming, 35th International Colloquium, 2008

An Efficient Algorithm for 2D Euclidean 2-Center with Outliers.
Proceedings of the Algorithms, 2008

2007
Value-Based Notification Conditions in Large-Scale Publish/Subscribe Systems.
Proceedings of the 33rd International Conference on Very Large Data Bases, 2007

Outlier Robust ICP for Minimizing Fractional RMSD.
Proceedings of the Sixth International Conference on 3-D Digital Imaging and Modeling, 2007

2006
Segmenting Motifs in Protein-Protein Interface Surfaces.
Proceedings of the Algorithms in Bioinformatics, 6th International Workshop, 2006

The hunting of the bump: on maximizing statistical discrepancy.
Proceedings of the Seventeenth Annual ACM-SIAM Symposium on Discrete Algorithms, 2006

Spatial scan statistics: approximations and performance study.
Proceedings of the Twelfth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2006

On Bipartite Matching under the RMS Distance.
Proceedings of the 18th Annual Canadian Conference on Computational Geometry, 2006

2004
Guided Expansive Spaces Trees: a Search Strategy for Motion- and Cost-constrained State Spaces.
Proceedings of the 2004 IEEE International Conference on Robotics and Automation, 2004

2002
Simulated Knot Tying.
Proceedings of the 2002 IEEE International Conference on Robotics and Automation, 2002


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