Thomas G. Dietterich
About
Thomas G. Dietterich has authored 138 papers that have received a total of 10.8k indexed citations.
This includes 87 papers in Artificial Intelligence, 22 papers in Computer Vision and Pattern Recognition and 14 papers in Computer Networks and Communications. The topics of these papers are Machine Learning and Algorithms (21 papers), Machine Learning and Data Classification (19 papers) and Reinforcement Learning in Robotics (17 papers). Thomas G. Dietterich is often cited by papers focused on Machine Learning and Algorithms (21 papers), Machine Learning and Data Classification (19 papers) and Reinforcement Learning in Robotics (17 papers) and collaborates with scholars based in United States, Germany and Australia. Thomas G. Dietterich's co-authors include Linda G. Shapiro, Prasad Tadepalli, Eric N. Mortensen, Andrew R. Moldenke and David A. Lytle and has published in prestigious journals such as Proceedings of the IEEE, Communications of the ACM and Ecological Economics
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