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Thomas Dietterich
Thomas Dietterich
Distinguished Professor (Emeritus), Computer Science, Oregon State University
Verified email at cs.orst.edu - Homepage
Title
Cited by
Cited by
Year
Ensemble methods in machine learning
TG Dietterich
International workshop on multiple classifier systems, 1-15, 2000
103892000
Approximate statistical tests for comparing supervised classification learning algorithms
TG Dietterich
Neural computation 10 (7), 1895-1923, 1998
44881998
Solving multiclass learning problems via error-correcting output codes
TG Dietterich, G Bakiri
Journal of artificial intelligence research 2, 263-286, 1994
38991994
An experimental comparison of three methods for constructing ensembles of decision trees: Bagging, boosting, and randomization
TG Dietterich
Machine learning 40, 139-157, 2000
38342000
Solving the multiple instance problem with axis-parallel rectangles
TG Dietterich, RH Lathrop, T Lozano-Pérez
Artificial intelligence 89 (1-2), 31-71, 1997
34541997
Benchmarking neural network robustness to common corruptions and perturbations
D Hendrycks, T Dietterich
arXiv preprint arXiv:1903.12261, 2019
31212019
Machine-learning research: Four Current Directions
TG Dietterich
AI magazine 18 (4), 97, 1997
21481997
Hierarchical reinforcement learning with the MAXQ value function decomposition
TG Dietterich
Journal of artificial intelligence research 13, 227-303, 2000
21062000
Deep anomaly detection with outlier exposure
D Hendrycks, M Mazeika, T Dietterich
arXiv preprint arXiv:1812.04606, 2018
14542018
Ensemble learning
TG Dietterich
The handbook of brain theory and neural networks 2 (1), 110-125, 2002
11012002
Learning with many irrelevant features
H Almuallim, TG Dietterich
Oregon State University, 1991
10241991
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
9852014
Overfitting and undercomputing in machine learning
T Dietterich
ACM computing surveys (CSUR) 27 (3), 326-327, 1995
9791995
Machine learning for sequential data: A review
TG Dietterich
Structural, Syntactic, and Statistical Pattern Recognition: Joint IAPR …, 2002
9742002
Machine learning
T Mitchell, B Buchanan, G DeJong, T Dietterich, P Rosenbloom, A Waibel
Annual review of computer science 4 (1), 417-433, 1990
878*1990
Pruning adaptive boosting
DD Margineantu, TG Dietterich
ICML 97, 211-218, 1997
7891997
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
7842021
To transfer or not to transfer
MT Rosenstein, Z Marx, LP Kaelbling, TG Dietterich
NIPS 2005 workshop on transfer learning 898 (3), 2005
7122005
Learning boolean concepts in the presence of many irrelevant features
H Almuallim, TG Dietterich
Artificial intelligence 69 (1-2), 279-305, 1994
7111994
Readings in machine learning
J Shavlik, T Dietterich
Morgan Kaufmann Publishers., 1990
625*1990
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