Gary William Flake
About
In The Last Decade
Gary William Flake
34 papers receiving 2.6k citations
Hit Papers
Peers
Comparison fields: 5 of 152
- Statistical and Nonlinear Physics 1.2k
- Artificial Intelligence 994
- Information Systems 933
- Computer Networks and Communications 590
- Computer Vision and Pattern Recognition 370
Countries citing papers authored by Gary William Flake
This map shows the geographic impact of Gary William Flake'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 Gary William Flake with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Gary William Flake more than expected).
Fields of papers citing papers by Gary William Flake
This network shows the impact of papers produced by Gary William Flake. 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 Gary William Flake. The network helps show where Gary William Flake may publish in the future.
Co-authorship network of co-authors of Gary William Flake
This figure shows the co-authorship network connecting the top 25 collaborators of Gary William Flake. A scholar is included among the top collaborators of Gary William Flake 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 Gary William Flake. Gary William Flake is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | Support Vector Machines for Regression Problems with Sequential Minimal Optimization | 2 |
| 2 | 19 | |
| 3 | Co-Validation: Using Model Disagreement on Unlabeled Data to Validate Classification Algorithms | 12 |
| 4 | The Self-organized Web: The Yin to the Semantic Web's Yang | 8 |
| 5 | 48 | |
| 6 | 40 | |
| 7 | 1 | |
| 8 | 65 | |
| 9 | 60 | |
| 10 | 72 | |
| 11 | 225 | |
| 12 | 3 | |
| 13 | 131 | |
| 14 | 33 | |
| 15 | Differentiating Functions of the Jacobian with Respect to the Weights | 3 |
| 16 | Heuristics for Improving the Performance of Online SVM Training Algorithms | 1 |
| 17 | The Computational Beauty of Nature | 150 |
| 18 | Exploiting Chaos to Control the Future | 1 |
| 19 | 83 | |
| 20 | 11 |
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.