Challenges in Deploying Machine Learning: A Survey of Case Studies
- Journal
- ACM Computing Surveys
In The Last Decade
doi.org/10.1145/3533378 →Countries where authors are citing Challenges in Deploying Machine Learning: A Survey of Case Studies
This map shows the geographic impact of Challenges in Deploying Machine Learning: A Survey of Case Studies. 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 Challenges in Deploying Machine Learning: A Survey of Case Studies with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Challenges in Deploying Machine Learning: A Survey of Case Studies more than expected).
Fields of papers citing Challenges in Deploying Machine Learning: A Survey of Case Studies
This network shows the impact of Challenges in Deploying Machine Learning: A Survey of Case Studies. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the Challenges in Deploying Machine Learning: A Survey of Case Studies.
About Challenges in Deploying Machine Learning: A Survey of Case Studies
This paper, published in 2022, received 259 indexed citations . Written by Andrei Paleyes, Raoul-Gabriel Urma and Neil D. Lawrence covering the research area of Artificial Intelligence. It is primarily cited by scholars working on Artificial Intelligence (117 citations), Information Systems (51 citations) and Computer Networks and Communications (45 citations). Published in ACM Computing Surveys.
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This paper is also available at doi.org/10.1145/3533378.