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
63292000
Solving multiclass learning problems via error-correcting output codes
TG Dietterich, G Bakiri
Journal of artificial intelligence research 2, 263-286, 1994
32861994
Approximate statistical tests for comparing supervised classification learning algorithms
TG Dietterich
Neural computation 10 (7), 1895-1923, 1998
31611998
Approximate statistical tests for comparing supervised classification learning algorithms
TG Dietterich
Neural computation 10 (7), 1895-1923, 1998
31611998
An experimental comparison of three methods for constructing ensembles of decision trees: Bagging, boosting, and randomization
TG Dietterich
Machine learning 40 (2), 139-157, 2000
28552000
Solving the multiple instance problem with axis-parallel rectangles
TG Dietterich, RH Lathrop, T Lozano-Pérez
Artificial intelligence 89 (1-2), 31-71, 1997
24661997
Machine-learning research: Four Current Directions
TG Dietterich
AI magazine 18 (4), 97, 1997
18421997
Hierarchical reinforcement learning with the MAXQ value function decomposition
TG Dietterich
Journal of artificial intelligence research 13, 227-303, 2000
14932000
Learning with many irrelevant features
H Almuallim, TG Dietterich
Oregon State University, 1991
9611991
Machine learning for sequential data: A review
TG Dietterich
Joint IAPR international workshops on statistical techniques in pattern …, 2002
6972002
Pruning adaptive boosting
DD Margineantu, TG Dietterich
ICML 97, 211-218, 1997
6341997
Learning boolean concepts in the presence of many irrelevant features
H Almuallim, TG Dietterich
Artificial intelligence 69 (1-2), 279-305, 1994
6051994
Ensemble learning
TG Dietterich
The handbook of brain theory and neural networks 2, 110-125, 2002
5662002
Readings in machine learning
J Shavlik, T Dietterich
Morgan Kaufmann Publishers., 1990
506*1990
Error-Correcting Output Coding Corrects Bias and Variance
EB Kong, TG Dietterich
Machine Learning Proceedings 1995: Proceedings of the Twelfth International …, 1995
4791995
A reinforcement learning approach to job-shop scheduling
W Zhang, TG Dietterich
IJCAI 95, 1114-1120, 1995
4641995
A comparative review of selected methods for learning from examples
TG Dietterich, RS Michalski
Machine learning, 41-81, 1983
4621983
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
4302014
A model of the mechanical design process based on empirical data
DG Ullman, TG Dietterich, LA Stauffer
Ai Edam 2 (1), 33-52, 1988
4101988
The MAXQ Method for Hierarchical Reinforcement Learning.
TG Dietterich
ICML 98, 118-126, 1998
3531998
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