Članki z zahtevami za javni dostop - Thomas DietterichVeč o tem
Ni na voljo nikjer: 3
Discovering anomalies by incorporating feedback from an expert
S Das, WK Wong, T Dietterich, A Fern, A Emmott
ACM Transactions on Knowledge Discovery from Data (TKDD) 14 (4), 1-32, 2020
Zahteve: US National Science Foundation, US Department of Defense
Optimal spatial-dynamic management of stochastic species invasions
KM Hall, HJ Albers, M Alkaee Taleghan, TG Dietterich
Environmental and Resource Economics 70, 403-427, 2018
Zahteve: US National Science Foundation
Connecting Conservation Research and Implementation
S McGregor, RM Houtman, R Metoyer, TG Dietterich
Artificial Intelligence and Conservation, 151, 2019
Zahteve: US National Science Foundation
Na voljo nekje: 24
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
Zahteve: US Department of Defense, German Research Foundation, Federal Ministry of …
Steps toward robust artificial intelligence
TG Dietterich
Ai Magazine 38 (3), 3-24, 2017
Zahteve: US National Science Foundation
Computational sustainability: Computing for a better world and a sustainable future
C Gomes, T Dietterich, C Barrett, J Conrad, B Dilkina, S Ermon, F Fang, ...
Communications of the ACM 62 (9), 56-65, 2019
Zahteve: US National Science Foundation
Open category detection with PAC guarantees
S Liu, R Garrepalli, T Dietterich, A Fern, D Hendrycks
International Conference on Machine Learning, 3169-3178, 2018
Zahteve: US National Science Foundation
Feedback-guided anomaly discovery via online optimization
MA Siddiqui, A Fern, TG Dietterich, R Wright, A Theriault, DW Archer
Proceedings of the 24th ACM SIGKDD international conference on knowledge …, 2018
Zahteve: US Department of Defense
Sequential feature explanations for anomaly detection
MA Siddiqui, A Fern, TG Dietterich, WK Wong
ACM Transactions on Knowledge Discovery from Data (TKDD) 13 (1), 1-22, 2019
Zahteve: US National Science Foundation, US Department of Defense
The familiarity hypothesis: Explaining the behavior of deep open set methods
TG Dietterich, A Guyer
Pattern Recognition 132, 108931, 2022
Zahteve: US Department of Defense
Confidence calibration for domain generalization under covariate shift
Y Gong, X Lin, Y Yao, TG Dietterich, A Divakaran, M Gervasio
Proceedings of the IEEE/CVF international conference on computer vision …, 2021
Zahteve: US Department of Defense
Spatial interactions and optimal forest management on a fire-threatened landscape
CJ Lauer, CA Montgomery, TG Dietterich
Forest Policy and Economics 83, 107-120, 2017
Zahteve: US National Science Foundation
Anomaly detection in the presence of missing values for weather data quality control
T Zemicheal, TG Dietterich
Proceedings of the 2nd ACM SIGCAS Conference on Computing and Sustainable …, 2019
Zahteve: US National Science Foundation
The role of restoration and key ecological invasion mechanisms in optimal spatial-dynamic management of invasive species
HJ Albers, KM Hall, KD Lee, MA Taleghan, TG Dietterich
Ecological Economics 151, 44-54, 2018
Zahteve: US National Science Foundation
Interactive visualization for testing markov decision processes: MDPVIS
S McGregor, H Buckingham, TG Dietterich, R Houtman, C Montgomery, ...
Journal of visual languages & computing 39, 93-106, 2017
Zahteve: US National Science Foundation
Sample-based tree search with fixed and adaptive state abstractions
J Hostetler, A Fern, T Dietterich
Journal of Artificial Intelligence Research 60, 717-777, 2017
Zahteve: US National Science Foundation
Efficient Exploration for Constrained MDPs.
MA Taleghan, TG Dietterich
AAAI Spring Symposia, 2018
Zahteve: US National Science Foundation
Crowds replicate performance of scientific experts scoring phylogenetic matrices of phenotypes
MA O’Leary, K Alphonse, AH Mariangeles, D Cavaliere, A Cirranello, ...
Systematic Biology 67 (1), 49-60, 2018
Zahteve: US National Science Foundation
Pac guarantees and effective algorithms for detecting novel categories
S Liu, R Garrepalli, D Hendrycks, A Fern, D Mondal, TG Dietterich
Journal of Machine Learning Research 23 (44), 1-47, 2022
Zahteve: US National Science Foundation, US Department of Defense
Managing fragmented fire-threatened landscapes with spatial externalities
CJ Lauer, CA Montgomery, TG Dietterich
Forest Science 66 (4), 443-456, 2020
Zahteve: US National Science Foundation, US National Oceanic and Atmospheric …
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