Thomas G. Dietterich

Author

Also Known As

Dietterich, Thomas, Dietterich, Thomas G., Dietterich, Tom, T Dietterich, T. Dietterich, T. G. Dietterich, T.G. Dietterich, Thomas Dietterich, Thomas G Dietterich, Thomas G. Dietterich

296

Publications

35.2K

Citations

H-Index

239

Concepts

All Affiliations

Oregon State University University of Washington

About

Thomas G. Dietterich is an author at Oregon State University specializing in engineering, computer science, and machine learning.

Top Concepts

#	Concept	H-Index	Publications	Citations
1	Engineering	47	90	18.5K
2	Management	14	16	1.1K
3	Education	6	6	4.1K
4	Language Studies	6	6	438
5	Business	3	3	78

Thomas G. Dietterich

133

Publications

23.4K

Citations

H-Index

Page 1

	Year	Citations
Approximate Statistical Tests for Comparing Supervised Classification Learning Algorithms Thomas G. Dietterich Neural Computation Approximate Statistical TestsEngineeringMachine LearningComparative TestLearning Algorithm	1998	3.5K
An Experimental Comparison of Three Methods for Constructing Ensembles of Decision Trees: Bagging, Boosting, and Randomization Thomas G. Dietterich Machine Learning EngineeringMachine LearningData ScienceData MiningMultiple Classifier System	2000	2.9K
Solving the multiple instance problem with axis-parallel rectangles Thomas G. Dietterich, Richard H. Lathrop, Tomás Lozano‐Pérez Artificial Intelligence Mathematical ProgrammingInstance-based LearningMultiple Instance LearningMachine VisionEngineering	1997	2.8K
Proceedings of the 13th International Conference on Neural Information Processing Systems Todd K. Leen, Thomas G. Dietterich, Volker Tresp Intelligent Information ProcessingEngineeringMachine LearningComputational NeuroscienceNeural Recoding	2000	2.2K
Benchmarking Neural Network Robustness to Common Corruptions and\n Perturbations Dan Hendrycks, Thomas G. Dietterich arXiv (Cornell University)	2019	783
Learning with many irrelevant features Hussein Almuallim, Thomas G. Dietterich National Conference on Artificial Intelligence	1991	610
Learning Boolean concepts in the presence of many irrelevant features Hussein Almuallim, Thomas G. Dietterich Artificial Intelligence Artificial IntelligenceSymbolic LearningEngineeringMachine LearningData Science	1994	519
Pruning Adaptive Boosting Dragos D. Margineantu, Thomas G. Dietterich	1997	512
Deep Anomaly Detection with Outlier Exposure Dan Hendrycks, Mantas Mazeika, Thomas G. Dietterich arXiv (Cornell University) Natural Language ProcessingAnomaly DetectionMachine LearningData ScienceData Mining	2018	401
A reinforcement learning approach to job-shop scheduling Wei Zhang, Thomas G. Dietterich	1995	375

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