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Thomas Dietterich
Thomas Dietterich
Distinguished Professor (Emeritus), Computer Science, Oregon State University
Adresse e-mail validée de cs.orst.edu - Page d'accueil
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Ensemble methods in machine learning
TG Dietterich
International workshop on multiple classifier systems, 1-15, 2000
113902000
Approximate statistical tests for comparing supervised classification learning algorithms
TG Dietterich
Neural computation 10 (7), 1895-1923, 1998
47481998
An experimental comparison of three methods for constructing ensembles of decision trees: Bagging, boosting, and randomization
TG Dietterich
Machine learning 40, 139-157, 2000
40012000
Solving multiclass learning problems via error-correcting output codes
TG Dietterich, G Bakiri
Journal of artificial intelligence research 2, 263-286, 1994
39611994
Benchmarking neural network robustness to common corruptions and perturbations
D Hendrycks, T Dietterich
arXiv preprint arXiv:1903.12261, 2019
39292019
Solving the multiple instance problem with axis-parallel rectangles
TG Dietterich, RH Lathrop, T Lozano-Pérez
Artificial intelligence 89 (1-2), 31-71, 1997
36441997
Hierarchical reinforcement learning with the MAXQ value function decomposition
TG Dietterich
Journal of artificial intelligence research 13, 227-303, 2000
22292000
Machine-learning research: Four Current Directions
TG Dietterich
AI magazine 18 (4), 97, 1997
21851997
Deep anomaly detection with outlier exposure
D Hendrycks, M Mazeika, T Dietterich
arXiv preprint arXiv:1812.04606, 2018
17942018
Ensemble learning
TG Dietterich
The handbook of brain theory and neural networks 2 (1), 110-125, 2002
1352*2002
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
11442014
Overfitting and undercomputing in machine learning
T Dietterich
ACM computing surveys (CSUR) 27 (3), 326-327, 1995
11311995
Learning with many irrelevant features
H Almuallim, TG Dietterich
Oregon State University, 1991
10911991
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
10902021
Machine learning for sequential data: A review
TG Dietterich
Structural, Syntactic, and Statistical Pattern Recognition: Joint IAPR …, 2002
10192002
Pruning adaptive boosting
DD Margineantu, TG Dietterich
ICML 97, 211-218, 1997
8311997
Understanding the psychology behind physician attitudes, behaviors, and engagement as the pathway to physician well-being
AH Rosenstein
Journal of Psychology & Clinical Psychiatry 5 (6), 1-3, 2016
7612016
Learning boolean concepts in the presence of many irrelevant features
H Almuallim, TG Dietterich
Artificial intelligence 69 (1-2), 279-305, 1994
7251994
A reinforcement learning approach to job-shop scheduling
W Zhang, TG Dietterich
Ijcai 95, 1114-1120, 1995
6481995
Readings in machine learning
J Shavlik, T Dietterich
Morgan Kaufmann Publishers., 1990
6381990
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