Virginia Smith
About
In The Last Decade
Virginia Smith
17 papers receiving 628 citations
Peers
Comparison fields: 5 of 69
- Artificial Intelligence 511
- Computer Networks and Communications 179
- Electrical and Electronic Engineering 103
- Computer Vision and Pattern Recognition 85
- Computer Science Applications 83
Countries citing papers authored by Virginia Smith
This map shows the geographic impact of Virginia Smith'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 Virginia Smith with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Virginia Smith more than expected).
Fields of papers citing papers by Virginia Smith
This network shows the impact of papers produced by Virginia Smith. 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 Virginia Smith. The network helps show where Virginia Smith may publish in the future.
Co-authorship network of co-authors of Virginia Smith
This figure shows the co-authorship network connecting the top 25 collaborators of Virginia Smith. A scholar is included among the top collaborators of Virginia Smith 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 Virginia Smith. Virginia Smith is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 0 | |
| 3 | 4 | |
| 4 | 5 | |
| 5 | 0 | |
| 6 | Tilted Empirical Risk Minimization | 16 |
| 7 | Ditto: Fair and Robust Federated Learning Through Personalization | 3 |
| 8 | 7 | |
| 9 | 53 | |
| 10 | Federated Multi-Task Learning for Competing Constraints. | 5 |
| 11 | Fair Resource Allocation in Federated Learning | 52 |
| 12 | On the Convergence of Federated Optimization in Heterogeneous Networks. | 135 |
| 13 | 80 | |
| 14 | System-Aware Optimization for Machine Learning at Scale | 1 |
| 15 | 1 | |
| 16 | Communication-Efficient Distributed Dual Coordinate Ascent | 51 |
| 17 | 17 | |
| 18 | 8 | |
| 19 | 90 | |
| 20 | Guidelines for Environmental Performance Measurements | 1 |
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.