Jeff M. Phillips
About
In The Last Decade
Jeff M. Phillips
65 papers receiving 1.3k citations
Peers
Comparison fields: 5 of 113
- Artificial Intelligence 505
- Computer Vision and Pattern Recognition 408
- Signal Processing 342
- Computer Networks and Communications 289
- Aerospace Engineering 172
Countries citing papers authored by Jeff M. Phillips
This map shows the geographic impact of Jeff M. Phillips's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Jeff M. Phillips with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jeff M. Phillips more than expected).
Fields of papers citing papers by Jeff M. Phillips
This network shows the impact of papers produced by Jeff M. Phillips. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Jeff M. Phillips. The network helps show where Jeff M. Phillips may publish in the future.
Co-authorship network of co-authors of Jeff M. Phillips
This figure shows the co-authorship network connecting the top 25 collaborators of Jeff M. Phillips. A scholar is included among the top collaborators of Jeff M. Phillips based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Jeff M. Phillips. Jeff M. Phillips is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Title | Journal | Authors | Indexed citations |
|---|---|---|---|---|
| 1 | Zombie Hashing: Reanimating Tombstones in Graveyard | Proceedings of the ACM on Management of Data | Jeff M. Phillips, Prashant Pandey et al. | 0 |
| 2 | Fast Comparative Analysis of Merge Trees Using Locality Sensitive Hashing | IEEE Transactions on Visualization and Computer Graphics | Jeff M. Phillips, Bei Wang et al. | 1 |
| 3 | Mitigating Exploitation Bias in Learning to Rank with an Uncertainty-aware Empirical Bayes Approach | Parth Gupta, Jeff M. Phillips et al. | 3 | |
| 4 | Ferret: Reviewing Tabular Datasets for Manipulation | Computer Graphics Forum | Jeff M. Phillips, Alexander Lex et al. | 2 |
| 5 | An Efficient Content-based Time Series Retrieval System | Chin‐Chia Michael Yeh, Huiyuan Chen et al. | 0 | |
| 6 | Predicting intent behind selections in scatterplot visualizations | Information Visualization | Carolina Nobre, Oliver Deußen et al. | 14 |
| 7 | 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 | Sunipa Dev, Jeff M. Phillips et al. | 79 |
| 8 | Semantic embedding for regions of interest | The VLDB Journal | Feifei Li, Jeff M. Phillips et al. | 7 |
| 9 | Self-Adaptable Point Processes with Nonparametric Time Decays | Neural Information Processing Systems | Jeff M. Phillips, Shandian Zhe et al. | 1 |
| 10 | A Visual Tour of Bias Mitigation Techniques for Word Representations | Sunipa Dev, Jeff M. Phillips et al. | 2 | |
| 11 | Independent Range Sampling, Revisited Again | DROPS (Schloss Dagstuhl – Leibniz Center for Informatics) | Peyman Afshani, Jeff M. Phillips | 4 |
| 12 | Visualization of Big Spatial Data Using Coresets for Kernel Density Estimates | IEEE Transactions on Big Data | Yan Zheng, Alexander Lex et al. | 11 |
| 13 | Relative Error Embeddings of the Gaussian Kernel Distance. | Jeff M. Phillips et al. | 0 | |
| 14 | ε-Kernel Coresets for Stochastic Points | Digital Commons - USU (Utah State University) | Haitao Wang, Lingxiao Huang et al. | 5 |
| 15 | Mergeable summaries | ACM Transactions on Database Systems | Pankaj K. Agarwal, Graham Cormode et al. | 78 |
| 16 | Uncertainty visualization in HARDI based on ensembles of ODFs | PubMed | Jeff M. Phillips, Yaniv Gur et al. | 25 |
| 17 | Generating a diverse set of high-quality clusterings | Jeff M. Phillips, Suresh Venkatasubramanian et al. | 2 | |
| 18 | Value-based notification conditions in large-scale publish/subscribe systems? | Very Large Data Bases | Badrish Chandramouli, Jeff M. Phillips et al. | 10 |
| 19 | The hunting of the bump: on maximizing statistical discrepancy | Symposium on Discrete Algorithms | Deepak Agarwal, Jeff M. Phillips et al. | 25 |
| 20 | On Bipartite Matching under the RMS Distance | Canadian Conference on Computational Geometry | Jeff M. Phillips, Pankaj K. Agarwal | 6 |
Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.