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Deep Convolution for Irregularly Sampled Temporal Point Clouds


May 01, 2021
Erich Merrill, Stefan Lee, Li Fuxin, Thomas G. Dietterich, Alan Fern

* 12 pages, submitted to ICLR 2021 

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Confidence Calibration for Domain Generalization under Covariate Shift


Apr 01, 2021
Yunye Gong, Xiao Lin, Yi Yao, Thomas G. Dietterich, Ajay Divakaran, Melinda Gervasio


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Three-quarter Sibling Regression for Denoising Observational Data


Dec 31, 2020
Shiv Shankar, Daniel Sheldon, Tao Sun, John Pickering, Thomas G. Dietterich

* IJCAI 2019 

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A Unifying Review of Deep and Shallow Anomaly Detection


Sep 28, 2020
Lukas Ruff, Jacob R. Kauffmann, Robert A. Vandermeulen, Grégoire Montavon, Wojciech Samek, Marius Kloft, Thomas G. Dietterich, Klaus-Robert Müller

* 36 pages, preprint; references added 

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Deep Anomaly Detection with Outlier Exposure


Dec 21, 2018
Dan Hendrycks, Mantas Mazeika, Thomas G. Dietterich

* ICLR 2019; PyTorch code available at https://github.com/hendrycks/outlier-exposure 

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Robust Artificial Intelligence and Robust Human Organizations


Nov 27, 2018
Thomas G. Dietterich

* To appear as a Perspective in Frontiers in Computer Science 

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Learning Scripts as Hidden Markov Models


Sep 11, 2018
J. Walker Orr, Prasad Tadepalli, Janardhan Rao Doppa, Xiaoli Fern, Thomas G. Dietterich

* 7 pages, AAAI 2014 

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Anomaly Detection in the Presence of Missing Values


Sep 05, 2018
Thomas G. Dietterich, Tadesse Zemicheal


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Open Category Detection with PAC Guarantees


Aug 01, 2018
Si Liu, Risheek Garrepalli, Thomas G. Dietterich, Alan Fern, Dan Hendrycks


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Benchmarking Neural Network Robustness to Common Corruptions and Surface Variations


Jul 04, 2018
Dan Hendrycks, Thomas G. Dietterich

* Datasets and PyTorch code available at https://github.com/hendrycks/robustness 

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Discovering and Removing Exogenous State Variables and Rewards for Reinforcement Learning


Jun 05, 2018
Thomas G. Dietterich, George Trimponias, Zhitang Chen

* To appear at ICML 2018 

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Factoring Exogenous State for Model-Free Monte Carlo


Nov 03, 2017
Sean McGregor, Rachel Houtman, Claire Montgomery, Ronald Metoyer, Thomas G. Dietterich

* 9 pages, 5 figures. Corrected equation 4 

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Incorporating Feedback into Tree-based Anomaly Detection


Aug 30, 2017
Shubhomoy Das, Weng-Keen Wong, Alan Fern, Thomas G. Dietterich, Md Amran Siddiqui

* 8 Pages, KDD 2017 Workshop on Interactive Data Exploration and Analytics (IDEA'17), August 14th, 2017, Halifax, Nova Scotia, Canada 

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Fast Optimization of Wildfire Suppression Policies with SMAC


Mar 28, 2017
Sean McGregor, Rachel Houtman, Claire Montgomery, Ronald Metoyer, Thomas G. Dietterich


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Transductive Optimization of Top k Precision


Oct 20, 2015
Li-Ping Liu, Thomas G. Dietterich, Nan Li, Zhi-Hua Zhou


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Sequential Feature Explanations for Anomaly Detection


Feb 28, 2015
Md Amran Siddiqui, Alan Fern, Thomas G. Dietterich, Weng-Keen Wong

* 9 pages, 4 figures and submitted to KDD 2015 

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Gaussian Approximation of Collective Graphical Models


May 20, 2014
Li-Ping Liu, Daniel Sheldon, Thomas G. Dietterich

* Accepted by ICML 2014. 10 page version with appendix 

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Inferring Strategies from Limited Reconnaissance in Real-time Strategy Games


Oct 16, 2012
Jesse Hostetler, Ethan W. Dereszynski, Thomas G. Dietterich, Alan Fern

* Appears in Proceedings of the Twenty-Eighth Conference on Uncertainty in Artificial Intelligence (UAI2012) 

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Active Imitation Learning via Reduction to I.I.D. Active Learning


Oct 16, 2012
Kshitij Judah, Alan Fern, Thomas G. Dietterich

* Appears in Proceedings of the Twenty-Eighth Conference on Uncertainty in Artificial Intelligence (UAI2012) 

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Learning from Sparse Data by Exploiting Monotonicity Constraints


Jul 04, 2012
Eric E. Altendorf, Angelo C. Restificar, Thomas G. Dietterich

* Appears in Proceedings of the Twenty-First Conference on Uncertainty in Artificial Intelligence (UAI2005) 

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Probabilistic Models for Anomaly Detection in Remote Sensor Data Streams


Jun 20, 2012
Ethan W. Dereszynski, Thomas G. Dietterich

* Appears in Proceedings of the Twenty-Third Conference on Uncertainty in Artificial Intelligence (UAI2007) 

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State Abstraction in MAXQ Hierarchical Reinforcement Learning


May 21, 1999
Thomas G. Dietterich

* 7 pages, 2 figures 

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Hierarchical Reinforcement Learning with the MAXQ Value Function Decomposition


May 21, 1999
Thomas G. Dietterich

* 63 pages, 15 figures 

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