Overfitting in Neural Nets: Backpropagation, Conjugate Gradient, and Early Stopping
- Journal
- Neural Information Processing Systems
In The Last Decade
doi.org/w6368295 →Countries where authors are citing Overfitting in Neural Nets: Backpropagation, Conjugate Gradient, and Early Stopping
This map shows the geographic impact of Overfitting in Neural Nets: Backpropagation, Conjugate Gradient, and Early Stopping. 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 Overfitting in Neural Nets: Backpropagation, Conjugate Gradient, and Early Stopping with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Overfitting in Neural Nets: Backpropagation, Conjugate Gradient, and Early Stopping more than expected).
Fields of papers citing Overfitting in Neural Nets: Backpropagation, Conjugate Gradient, and Early Stopping
This network shows the impact of Overfitting in Neural Nets: Backpropagation, Conjugate Gradient, and Early Stopping. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the Overfitting in Neural Nets: Backpropagation, Conjugate Gradient, and Early Stopping.
About Overfitting in Neural Nets: Backpropagation, Conjugate Gradient, and Early Stopping
This paper, published in 2000, received 586 indexed citations . Written by Rich Caruana, Steve Lawrence and C. Lee Giles covering the research area of Artificial Intelligence and Computer Vision and Pattern Recognition. It is primarily cited by scholars working on Artificial Intelligence (266 citations), Computer Vision and Pattern Recognition (101 citations), Control and Systems Engineering (49 citations), Electrical and Electronic Engineering (44 citations) and Signal Processing (42 citations). Published in Neural Information Processing Systems.
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.
This paper is also available at doi.org/w6368295.