Proceedings of the 25th international conference on Machine learning
- Journal
- International Conference on Machine Learning
In The Last Decade
doi.org/w8154475 →Countries where authors are citing Proceedings of the 25th international conference on Machine learning
This map shows the geographic impact of Proceedings of the 25th international conference on Machine learning. 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 Proceedings of the 25th international conference on Machine learning with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Proceedings of the 25th international conference on Machine learning more than expected).
Fields of papers citing Proceedings of the 25th international conference on Machine learning
This network shows the impact of Proceedings of the 25th international conference on Machine learning. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the Proceedings of the 25th international conference on Machine learning.
About Proceedings of the 25th international conference on Machine learning
This paper, published in 2008, received 4.4k indexed citations . Written by William W. Cohen, Andrew McCallum and Sam T. Roweis covering the research area of Artificial Intelligence and Statistics and Probability. It is primarily cited by scholars working on Artificial Intelligence (2.4k citations), Computer Vision and Pattern Recognition (1.2k citations) and Information Systems (438 citations). Published in International Conference on Machine Learning.
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/w8154475.