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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
110412000
Approximate statistical tests for comparing supervised classification learning algorithms
TG Dietterich
Neural computation 10 (7), 1895-1923, 1998
46761998
An experimental comparison of three methods for constructing ensembles of decision trees: Bagging, boosting, and randomization
TG Dietterich
Machine learning 40, 139-157, 2000
39452000
Solving multiclass learning problems via error-correcting output codes
TG Dietterich, G Bakiri
Journal of artificial intelligence research 2, 263-286, 1994
39391994
Benchmarking neural network robustness to common corruptions and perturbations
D Hendrycks, T Dietterich
arXiv preprint arXiv:1903.12261, 2019
36632019
Solving the multiple instance problem with axis-parallel rectangles
TG Dietterich, RH Lathrop, T Lozano-Pérez
Artificial intelligence 89 (1-2), 31-71, 1997
35821997
Hierarchical reinforcement learning with the MAXQ value function decomposition
TG Dietterich
Journal of artificial intelligence research 13, 227-303, 2000
21692000
Machine-learning research: Four Current Directions
TG Dietterich
AI magazine 18 (4), 97, 1997
21691997
Deep anomaly detection with outlier exposure
D Hendrycks, M Mazeika, T Dietterich
arXiv preprint arXiv:1812.04606, 2018
16832018
Ensemble learning
TG Dietterich
The handbook of brain theory and neural networks 2 (1), 110-125, 2002
1306*2002
Overfitting and undercomputing in machine learning
T Dietterich
ACM computing surveys (CSUR) 27 (3), 326-327, 1995
10901995
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
10842014
Learning with many irrelevant features
H Almuallim, TG Dietterich
Oregon State University, 1991
10831991
Machine learning for sequential data: A review
TG Dietterich
Structural, Syntactic, and Statistical Pattern Recognition: Joint IAPR …, 2002
10132002
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
9862021
Pruning adaptive boosting
DD Margineantu, TG Dietterich
ICML 97, 211-218, 1997
8211997
To transfer or not to transfer
MT Rosenstein, Z Marx, LP Kaelbling, TG Dietterich
NIPS 2005 workshop on transfer learning 898 (3), 4, 2005
7492005
Learning boolean concepts in the presence of many irrelevant features
H Almuallim, TG Dietterich
Artificial intelligence 69 (1-2), 279-305, 1994
7181994
A reinforcement learning approach to job-shop scheduling
W Zhang, TG Dietterich
Ijcai 95, 1114-1120, 1995
6401995
Readings in machine learning
J Shavlik, T Dietterich
Morgan Kaufmann Publishers., 1990
6341990
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