Thomas Dietterich

Получаване на мой собствен потребителски профил

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	Всички	От 2019
Позовавания	66461	28044
h-индекс	91	54
i10-индекс	236	142

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25 статии

4 статии

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Въз основа на изисквания при финансирането

Съавтори

Prasad TadepalliProfessor of Computer Science, Oregon State UniversityПотвърден имейл адрес: eecs.oregonstate.edu
Dan HendrycksDirector of the Center for AI SafetyПотвърден имейл адрес: berkeley.edu
Jon HerlockerCEO Tignis, incПотвърден имейл адрес: herlocker.org
David G. UllmanDavid Ullman LLC.Потвърден имейл адрес: davidullman.com
Linda ShapiroProfessor of Computer Science & Engineering, University of WashingtonПотвърден имейл адрес: cs.washington.edu
Richard H. LathropProfessor of Computer Science, University of California IrvineПотвърден имейл адрес: uci.edu
Hussein AlmuallimPresident, FirmSoft TechnologiesПотвърден имейл адрес: firmsofttech.com
Weng-Keen WongProfessor of Computer Science, Oregon State UniversityПотвърден имейл адрес: eecs.oregonstate.edu
Tomas Lozano-PerezProfessor of Computer Science, MITПотвърден имейл адрес: mit.edu
Nicholas S. FlannAssociate Professor of Computer Science, Utah State UniversityПотвърден имейл адрес: usu.edu
Jude ShavlikProfessor of Computer Science and of Biostatistics & Medical Informatics, University of WisconsinПотвърден имейл адрес: cs.wisc.edu
David A. LytleOregon State UniversityПотвърден имейл адрес: oregonstate.edu
Simone StumpfUniversity of GlasgowПотвърден имейл адрес: glasgow.ac.uk
Dragos D MargineantuBoeing Research & TechnologyПотвърден имейл адрес: boeing.com
Jianqiang ShenPalo Alto Research Center (PARC)Потвърден имейл адрес: parc.com
Xiaoli FernOregon State UniversityПотвърден имейл адрес: eecs.oregonstate.edu
Janardhan Rao (Jana) DoppaHuie-Rogers Endowed Chair Associate Professor, Washington State UniversityПотвърден имейл адрес: eecs.wsu.edu
Hongli Dengprincipal applied scientistПотвърден имейл адрес: amazon.com
Claire MontgomeryEmeritus Professor, Oregon State University, College of ForestryПотвърден имейл адрес: oregonstate.edu
Daniel SheldonUniversity of Massachusetts AmherstПотвърден имейл адрес: cs.umass.edu

Следене

Thomas Dietterich

Distinguished Professor (Emeritus), Computer Science, Oregon State University

Потвърден имейл адрес: cs.orst.edu - Начална страница

Machine Learning Computational Sustainability Artificial Intelligence Reinforcement Learning


Заглавие Сортиране по цитати Сортиране по година Сортиране по заглавие	Позовавания Позовавания	Година
Ensemble methods in machine learning TG Dietterich International workshop on multiple classifier systems, 1-15, 2000	10952	2000
Approximate statistical tests for comparing supervised classification learning algorithms TG Dietterich Neural computation 10 (7), 1895-1923, 1998	4656	1998
Solving multiclass learning problems via error-correcting output codes TG Dietterich, G Bakiri Journal of artificial intelligence research 2, 263-286, 1994	3933	1994
An experimental comparison of three methods for constructing ensembles of decision trees: Bagging, boosting, and randomization TG Dietterich Machine learning 40, 139-157, 2000	3931	2000
Benchmarking neural network robustness to common corruptions and perturbations D Hendrycks, T Dietterich arXiv preprint arXiv:1903.12261, 2019	3607	2019
Solving the multiple instance problem with axis-parallel rectangles TG Dietterich, RH Lathrop, T Lozano-Pérez Artificial intelligence 89 (1-2), 31-71, 1997	3572	1997
Machine-learning research: Four Current Directions TG Dietterich AI magazine 18 (4), 97, 1997	2169	1997
Hierarchical reinforcement learning with the MAXQ value function decomposition TG Dietterich Journal of artificial intelligence research 13, 227-303, 2000	2163	2000
Deep anomaly detection with outlier exposure D Hendrycks, M Mazeika, T Dietterich arXiv preprint arXiv:1812.04606, 2018	1657	2018
Ensemble learning TG Dietterich The handbook of brain theory and neural networks 2 (1), 110-125, 2002	1300*	2002
Learning with many irrelevant features H Almuallim, TG Dietterich Oregon State University, 1991	1082	1991
Overfitting and undercomputing in machine learning T Dietterich ACM computing surveys (CSUR) 27 (3), 326-327, 1995	1077	1995
The eBird enterprise: An integrated approach to development and application of citizen science BL Sullivan, JL Aycrigg, JH Barry, RE Bonney, N Bruns, CB Cooper, ... Biological conservation 169, 31-40, 2014	1074	2014
Machine learning for sequential data: A review TG Dietterich Structural, Syntactic, and Statistical Pattern Recognition: Joint IAPR …, 2002	1010	2002
A unifying review of deep and shallow anomaly detection L Ruff, JR Kauffmann, RA Vandermeulen, G Montavon, W Samek, M Kloft, ... Proceedings of the IEEE 109 (5), 756-795, 2021	967	2021
Pruning adaptive boosting DD Margineantu, TG Dietterich ICML 97, 211-218, 1997	821	1997
To transfer or not to transfer MT Rosenstein, Z Marx, LP Kaelbling, TG Dietterich NIPS 2005 workshop on transfer learning 898 (3), 4, 2005	746	2005
Learning boolean concepts in the presence of many irrelevant features H Almuallim, TG Dietterich Artificial intelligence 69 (1-2), 279-305, 1994	718	1994
A reinforcement learning approach to job-shop scheduling W Zhang, TG Dietterich Ijcai 95, 1114-1120, 1995	638	1995
Readings in machine learning J Shavlik, T Dietterich Morgan Kaufmann Publishers., 1990	633	1990

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