Thomas G. Dietterich

236 papers A* 59A 16B 8C 5Journal 99Unranked 43

Year	Rank	Type	Title / Venue / Authors
2025	J	`jnl`	International AI Safety Report 2025: First Key Update: Capabilities and Risk Implications. CoRR Yoshua Bengio, Stephen Clare, Carina Prunkl, Shalaleh Rismani, Maksym Andriushchenko, Ben Bucknall, Philip Fox, Tiancheng Hu, Cameron Jones, Sam Manning, Nestor Maslej, Vasilios Mavroudis, Conor McGlynn, Malcolm Murray, Charlotte Stix, Lucia Velasco, Nicole Wheeler, Daniel Privitera, Sören Mindermann, Daron Acemoglu, Thomas G. Dietterich, Fredrik Heintz, Geoffrey E. Hinton, Nicholas R. Jennings, Susan Leavy, Teresa Ludermir, Vidushi Marda, Helen Margetts, John A. McDermid, Jane Munga, Arvind Narayanan, Alondra Nelson, Clara Neppel, Gopal Ramchurn, Stuart Russell, Marietje Schaake, Bernhard Schölkopf, Alavaro Soto, Lee Tiedrich, Gaël Varoquaux, Andrew Yao, Yan-Ning Zhang, Leandro Aguirre, Olubunmi Ajala, Fahad Albalawi Noora AlMalek, Christian Busch, André C. P. L. F. de Carvalho, Jonathan Collas, Amandeep Gill, Ahmet Halit Hatip, Juha Heikkilä, Chris Johnson, Gill Jolly, Ziv Katzir, Mary Kerema, Hiroaki Kitano, Antonio Krüger, Aoife McLysaght, Oleksii Molchanovskyi, Andrea Monti, Kyoung Mu Lee, Mona Nemer, Nuria Oliver, Raquel Pezoa Rivera, Audrey Plonk, José Ramón López Portillo, Balaraman Ravindran, Hammam Riza, Crystal Rugege, Haroon Sheikh, Denise Wong, Yi Zeng, Liming Zhu
2025	J	`jnl`	International AI Safety Report 2025: Second Key Update: Technical Safeguards and Risk Management. CoRR Yoshua Bengio, Stephen Clare, Carina Prunkl, Maksym Andriushchenko, Ben Bucknall, Philip Fox, Nestor Maslej, Conor McGlynn, Malcolm Murray, Shalaleh Rismani, Stephen Casper, Jessica Newman, Daniel Privitera, Sören Mindermann, Daron Acemoglu, Thomas G. Dietterich, Fredrik Heintz, Geoffrey E. Hinton, Nick R. Jennings, Susan Leavy, Teresa Ludermir, Vidushi Marda, Helen Margetts, John A. McDermid, Jane Munga, Arvind Narayanan, Alondra Nelson, Clara Neppel, Gopal Ramchurn, Stuart Russell, Marietje Schaake, Bernhard Schölkopf, Alavaro Soto, Lee Tiedrich, Gaël Varoquaux, Andrew Yao, Yanning Zhang, Leandro Aguirre, Olubunmi Ajala, Fahad Albalawi Noora AlMalek, Noora AlMalek, Christian Busch, André Carvalho, Jonathan Collas, Amandeep Gill, Ahmet Halit Hatip, Juha Heikkilä, Chris Johnson, Gill Jolly, Ziv Katzir, Mary Kerema, Hiroaki Kitano, Antonio Krüger, Aoife McLysaght, Oleksii Molchanovskyi, Andrea Monti, Kyoung Mu Lee, Mona Nemer, Nuria Oliver, Raquel Pezoa, Audrey Plonk, José Ramón López Portillo, Balaraman Ravindran, Hammam Riza, Crystal Rugege, Haroon Sheikh, Denise Wong, Yi Zeng, Liming Zhu
2025	J	`jnl`	International AI Safety Report. CoRR Yoshua Bengio, Sören Mindermann, Daniel Privitera, Tamay Besiroglu, Rishi Bommasani, Stephen Casper, Yejin Choi, Philip Fox, Ben Garfinkel, Danielle Goldfarb, Hoda Heidari, Anson Ho, Sayash Kapoor, Leila Khalatbari, Shayne Longpre, Sam Manning, Vasilios Mavroudis, Mantas Mazeika, Julian Michael, Jessica Newman, Kwan Yee Ng, Chinasa T. Okolo, Inioluwa Deborah Raji, Girish Sastry, Elizabeth Seger, Theodora Skeadas, Tobin South, Emma Strubell, Florian Tramèr, Lucia Velasco, Nicole Wheeler, Daron Acemoglu, Olubayo Adekanmbi, David Dalrymple, Thomas G. Dietterich, Edward W. Felten, Pascale Fung, Pierre-Olivier Gourinchas, Fredrik Heintz, Geoffrey E. Hinton, Nick R. Jennings, Andreas Krause, Susan Leavy, Percy Liang, Teresa Ludermir, Vidushi Marda, Helen Margetts, John A. McDermid, Jane Munga, Arvind Narayanan, Alondra Nelson, Clara Neppel, Alice Oh, Gopal Ramchurn, Stuart Russell, Marietje Schaake, Bernhard Schölkopf, Dawn Song, Alvaro Soto, Lee Tiedrich, Gaël Varoquaux, Andrew Yao, Ya-Qin Zhang, Fahad Albalawi, Marwan Alserkal, Olubunmi Ajala, Guillaume Avrin, Christian Busch, André Carlos Ponce de Leon Ferreira de Carvalho, Bronwyn Fox, Amandeep Singh Gill, Ahmet Halit Hatip, Juha Heikkilä, Gill Jolly, Ziv Katzir, Hiroaki Kitano, Antonio Krüger, Chris Johnson, Saif M. Khan, Kyoung Mu Lee, Dominic Vincent Ligot, Oleksii Molchanovskyi, Andrea Monti, Nusu Mwamanzi, Mona Nemer, Nuria Oliver, José Ramón López Portillo, Balaraman Ravindran, Raquel Pezoa Rivera, Hammam Riza, Crystal Rugege, Ciarán Seoighe, Jerry Sheehan, Haroon Sheikh, Denise Wong, Yi Zeng
2024	J	`jnl`	International Scientific Report on the Safety of Advanced AI (Interim Report). CoRR Yoshua Bengio, Sören Mindermann, Daniel Privitera, Tamay Besiroglu, Rishi Bommasani, Stephen Casper, Yejin Choi, Danielle Goldfarb, Hoda Heidari, Leila Khalatbari, Shayne Longpre, Vasilios Mavroudis, Mantas Mazeika, Kwan Yee Ng, Chinasa T. Okolo, Inioluwa Deborah Raji, Theodora Skeadas, Florian Tramèr, Bayo Adekanmbi, Paul F. Christiano, David Dalrymple, Thomas G. Dietterich, Edward W. Felten, Pascale Fung, Pierre-Olivier Gourinchas, Nick R. Jennings, Andreas Krause, Percy Liang, Teresa Ludermir, Vidushi Marda, Helen Margetts, John A. McDermid, Arvind Narayanan, Alondra Nelson, Alice Oh, Gopal Ramchurn, Stuart Russell, Marietje Schaake, Dawn Song, Alvaro Soto, Lee Tiedrich, Gaël Varoquaux, Andrew Yao, Ya-Qin Zhang
2023	J	`jnl`	Hidden Heterogeneity: When to Choose Similarity-Based Calibration. Trans. Mach. Learn. Res. Kiri L. Wagstaff, Thomas G. Dietterich
2023	J	`jnl`	Reinforcement Learning with Exogenous States and Rewards. CoRR George Trimponias, Thomas G. Dietterich
2022	A*	`conf`	ANDEA: Anomaly and Novelty Detection, Explanation, and Accommodation. KDD Guansong Pang, Jundong Li, Anton van den Hengel, Longbing Cao, Thomas G. Dietterich
2022	J	`jnl`	Conformal Prediction Intervals for Markov Decision Process Trajectories. CoRR Thomas G. Dietterich, Jesse Hostetler
2022	J	`jnl`	Hidden Heterogeneity: When to Choose Similarity-Based Calibration. CoRR Kiri L. Wagstaff, Thomas G. Dietterich
2022	J	`jnl`	Oracle Analysis of Representations for Deep Open Set Detection. CoRR Risheek Garrepalli, Alan Fern, Thomas G. Dietterich
2022	J	`jnl`	PAC Guarantees and Effective Algorithms for Detecting Novel Categories. J. Mach. Learn. Res. Si Liu, Risheek Garrepalli, Dan Hendrycks, Alan Fern, Debashis Mondal, Thomas G. Dietterich
2022	J	`jnl`	The Familiarity Hypothesis: Explaining the Behavior of Deep Open Set Methods. CoRR Thomas G. Dietterich, Alexander Guyer
2022	J	`jnl`	The familiarity hypothesis: Explaining the behavior of deep open set methods. Pattern Recognit. Thomas G. Dietterich, Alexander Guyer
2022	J	`jnl`	Will My Robot Achieve My Goals? Predicting the Probability that an MDP Policy Reaches a User-Specified Behavior Target. CoRR Alexander Guyer, Thomas G. Dietterich
2021	J	`jnl`	A Unifying Review of Deep and Shallow Anomaly Detection. Proc. IEEE Lukas Ruff, Jacob R. Kauffmann, Robert A. Vandermeulen, Grégoire Montavon, Wojciech Samek, Marius Kloft, Thomas G. Dietterich, Klaus-Robert Müller
2021	A*	`conf`	Anomaly and Novelty Detection, Explanation, and Accommodation (ANDEA). KDD Guansong Pang, Jundong Li, Anton van den Hengel, Longbing Cao, Thomas G. Dietterich
2021	A*	`conf`	Confidence Calibration for Domain Generalization under Covariate Shift. ICCV Yunye Gong, Xiao Lin, Yi Yao, Thomas G. Dietterich, Ajay Divakaran, Melinda T. Gervasio
2021	J	`jnl`	Confidence Calibration for Domain Generalization under Covariate Shift. CoRR Yunye Gong, Xiao Lin, Yi Yao, Thomas G. Dietterich, Ajay Divakaran, Melinda T. Gervasio
2021	J	`jnl`	Deep Convolution for Irregularly Sampled Temporal Point Clouds. CoRR Erich Merrill, Stefan Lee, Fuxin Li, Thomas G. Dietterich, Alan Fern
2021	A*	`conf`	K-N-MOMDPs: Towards Interpretable Solutions for Adaptive Management. AAAI Jonathan Ferrer-Mestres, Thomas G. Dietterich, Olivier Buffet, Iadine Chades
2021	J	`jnl`	Three-quarter Sibling Regression for Denoising Observational Data. CoRR Shiv Shankar, Daniel Sheldon, Tao Sun, John Pickering, Thomas G. Dietterich
2020	J	`jnl`	A Unifying Review of Deep and Shallow Anomaly Detection. CoRR Lukas Ruff, Jacob R. Kauffmann, Robert A. Vandermeulen, Grégoire Montavon, Wojciech Samek, Marius Kloft, Thomas G. Dietterich, Klaus-Robert Müller
2020	C	`conf`	Conditional mixture models for precipitation data quality control. COMPASS Tadesse Zemicheal, Thomas G. Dietterich
2020	J	`jnl`	DARPA's Role in Machine Learning. AI Mag. Joshua Alspector, Thomas G. Dietterich
2020	J	`jnl`	Discovering Anomalies by Incorporating Feedback from an Expert. ACM Trans. Knowl. Discov. Data Shubhomoy Das, Weng-Keen Wong, Thomas G. Dietterich, Alan Fern, Andrew Emmott
2020	A*	`conf`	Solving K-MDPs. ICAPS Jonathan Ferrer-Mestres, Thomas G. Dietterich, Olivier Buffet, Iadine Chadès
2019	C	`conf`	Anomaly detection in the presence of missing values for weather data quality control. COMPASS Tadesse Zemicheal, Thomas G. Dietterich
2019	—	`conf`	Benchmarking Neural Network Robustness to Common Corruptions and Perturbations. ICLR (Poster) Dan Hendrycks, Thomas G. Dietterich
2019	J	`jnl`	Benchmarking Neural Network Robustness to Common Corruptions and Perturbations. CoRR Dan Hendrycks, Thomas G. Dietterich
2019	J	`jnl`	Computational sustainability: computing for a better world and a sustainable future. Commun. ACM Carla P. Gomes, Thomas G. Dietterich, Christopher Barrett, Jon Conrad, Bistra Dilkina, Stefano Ermon, Fei Fang, Andrew Farnsworth, Alan Fern, Xiaoli Z. Fern, Daniel Fink, Douglas H. Fisher, Alexander Flecker, Daniel Freund, Angela Fuller, John M. Gregoire, John E. Hopcroft, Steve Kelling, J. Zico Kolter, Warren B. Powell, Nicole D. Sintov, John S. Selker, Bart Selman, Daniel Sheldon, David B. Shmoys, Milind Tambe, Weng-Keen Wong, Christopher Wood, Xiaojian Wu, Yexiang Xue, Amulya Yadav, Abdul-Aziz Yakubu, Mary Lou Zeeman
2019	—	`conf`	Deep Anomaly Detection with Outlier Exposure. ICLR (Poster) Dan Hendrycks, Mantas Mazeika, Thomas G. Dietterich
2019	J	`jnl`	Robust artificial intelligence and robust human organizations. Frontiers Comput. Sci. Thomas G. Dietterich
2019	J	`jnl`	Sequential Feature Explanations for Anomaly Detection. ACM Trans. Knowl. Discov. Data Md Amran Siddiqui, Alan Fern, Thomas G. Dietterich, Weng-Keen Wong
2019	A*	`conf`	Three-quarter Sibling Regression for Denoising Observational Data. IJCAI Shiv Shankar, Daniel Sheldon, Tao Sun, John Pickering, Thomas G. Dietterich
2018	J	`jnl`	Anomaly Detection in the Presence of Missing Values. CoRR Thomas G. Dietterich, Tadesse Zemicheal
2018	J	`jnl`	Benchmarking Neural Network Robustness to Common Corruptions and Perturbations. CoRR Dan Hendrycks, Thomas G. Dietterich
2018	—	`conf`	Can We Achieve Open Category Detection with Guarantees? AAAI Workshops Si Liu, Risheek Garrepalli, Alan Fern, Thomas G. Dietterich
2018	J	`jnl`	Deep Anomaly Detection with Outlier Exposure. CoRR Dan Hendrycks, Mantas Mazeika, Thomas G. Dietterich
2018	A*	`conf`	Discovering and Removing Exogenous State Variables and Rewards for Reinforcement Learning. ICML Thomas G. Dietterich, George Trimponias, Zhitang Chen
2018	J	`jnl`	Discovering and Removing Exogenous State Variables and Rewards for Reinforcement Learning. CoRR Thomas G. Dietterich, George Trimponias, Zhitang Chen
2018	—	`conf`	Efficient Exploration for Constrained MDPs. AAAI Spring Symposia Majid Alkaee Taleghan, Thomas G. Dietterich
2018	A*	`conf`	Feedback-Guided Anomaly Discovery via Online Optimization. KDD Md Amran Siddiqui, Alan Fern, Thomas G. Dietterich, Ryan Wright, Alec Theriault, David W. Archer
2018	J	`jnl`	Learning Scripts as Hidden Markov Models. CoRR John Walker Orr, Prasad Tadepalli, Janardhan Rao Doppa, Xiaoli Z. Fern, Thomas G. Dietterich
2018	A*	`conf`	Open Category Detection with PAC Guarantees. ICML Si Liu, Risheek Garrepalli, Thomas G. Dietterich, Alan Fern, Dan Hendrycks
2018	J	`jnl`	Open Category Detection with PAC Guarantees. CoRR Si Liu, Risheek Garrepalli, Thomas G. Dietterich, Alan Fern, Dan Hendrycks
2018	J	`jnl`	Robust Artificial Intelligence and Robust Human Organizations. CoRR Thomas G. Dietterich
2017	J	`jnl`	Factoring Exogenous State for Model-Free Monte Carlo. CoRR Sean McGregor, Rachel Houtman, Claire A. Montgomery, Ronald A. Metoyer, Thomas G. Dietterich
2017	J	`jnl`	Fast Optimization of Wildfire Suppression Policies with SMAC. CoRR Sean McGregor, Rachel Houtman, Claire A. Montgomery, Ronald A. Metoyer, Thomas G. Dietterich
2017	J	`jnl`	Incorporating Feedback into Tree-based Anomaly Detection. CoRR Shubhomoy Das, Weng-Keen Wong, Alan Fern, Thomas G. Dietterich, Md Amran Siddiqui
2017	J	`jnl`	Interactive visualization for testing Markov Decision Processes: MDPVIS. J. Vis. Lang. Comput. Sean McGregor, Hailey Buckingham, Thomas G. Dietterich, Rachel Houtman, Claire A. Montgomery, Ronald A. Metoyer
2017	J	`jnl`	Sample-Based Tree Search with Fixed and Adaptive State Abstractions. J. Artif. Intell. Res. Jesse Hostetler, Alan Fern, Thomas G. Dietterich
2017	J	`jnl`	Steps Toward Robust Artificial Intelligence. AI Mag. Thomas G. Dietterich
2016	A	`conf`	Finite Sample Complexity of Rare Pattern Anomaly Detection. UAI Md Amran Siddiqui, Alan Fern, Thomas G. Dietterich, Shubhomoy Das
2016	A*	`conf`	Incorporating Expert Feedback into Active Anomaly Discovery. ICDM Shubhomoy Das, Weng-Keen Wong, Thomas G. Dietterich, Alan Fern, Andrew Emmott
2016	A*	`conf`	Transductive Optimization of Top k Precision. IJCAI Li-Ping Liu, Thomas G. Dietterich, Nan Li, Zhi-Hua Zhou
2015	B	`conf`	Facilitating testing and debugging of Markov Decision Processes with interactive visualization. VL/HCC Sean McGregor, Hailey Buckingham, Thomas G. Dietterich, Rachel Houtman, Claire A. Montgomery, Ronald A. Metoyer
2015	B	`conf`	Facilitating testing and debugging of Markov Decision Processes with interactive visualization. VL/HCC Sean McGregor, Hailey Buckingham, Thomas G. Dietterich, Rachel Houtman, Claire A. Montgomery, Ronald A. Metoyer
2015	A*	`conf`	Improving Automated Email Tagging with Implicit Feedback. UIST Mohammad S. Sorower, Michael Slater, Thomas G. Dietterich
2015	A*	`conf`	Learning Greedy Policies for the Easy-First Framework. AAAI Jun Xie, Chao Ma, Janardhan Rao Doppa, Prashanth Mannem, Xiaoli Z. Fern, Thomas G. Dietterich, Prasad Tadepalli
2015	—	`conf`	MDPVIS: An Interactive Visualization for Testing Markov Decision Processes. AAAI Fall Symposia Sean McGregor, Hailey Buckingham, Rachel Houtman, Claire A. Montgomery, Ronald A. Metoyer, Thomas G. Dietterich
2015	J	`jnl`	PAC optimal MDP planning with application to invasive species management. J. Mach. Learn. Res. Majid Alkaee Taleghan, Thomas G. Dietterich, Mark Crowley, Kim Hall, H. Jo Albers
2015	A	`conf`	Progressive Abstraction Refinement for Sparse Sampling. UAI Jesse Hostetler, Alan Fern, Thomas G. Dietterich
2015	J	`jnl`	Rise of concerns about AI: reflections and directions. Commun. ACM Thomas G. Dietterich, Eric Horvitz
2015	J	`jnl`	Sequential Feature Explanations for Anomaly Detection. CoRR Md Amran Siddiqui, Alan Fern, Thomas G. Dietterich, Weng-Keen Wong
2015	J	`jnl`	Systematic Construction of Anomaly Detection Benchmarks from Real Data. CoRR Andrew Emmott, Shubhomoy Das, Thomas G. Dietterich, Alan Fern, Weng-Keen Wong
2015	J	`jnl`	Transductive Optimization of Top k Precision. CoRR Li-Ping Liu, Thomas G. Dietterich, Nan Li, Zhi-Hua Zhou
2015	A*	`conf`	ℋC-search for structured prediction in computer vision. CVPR Michael Lam, Janardhan Rao Doppa, Sinisa Todorovic, Thomas G. Dietterich
2014	J	`jnl`	Active lmitation learning: formal and practical reductions to I.I.D. learning. J. Mach. Learn. Res. Kshitij Judah, Alan Paul Fern, Thomas G. Dietterich, Prasad Tadepalli
2014	A*	`conf`	Gaussian Approximation of Collective Graphical Models. ICML Li-Ping Liu, Daniel Sheldon, Thomas G. Dietterich
2014	J	`jnl`	Gaussian Approximation of Collective Graphical Models. CoRR Li-Ping Liu, Daniel Sheldon, Thomas G. Dietterich
2014	A*	`conf`	Learnability of the Superset Label Learning Problem. ICML Li-Ping Liu, Thomas G. Dietterich
2014	A*	`conf`	Learning Scripts as Hidden Markov Models. AAAI John Walker Orr, Prasad Tadepalli, Janardhan Rao Doppa, Xiaoli Z. Fern, Thomas G. Dietterich
2014	A*	`conf`	Prune-and-Score: Learning for Greedy Coreference Resolution. EMNLP Chao Ma, Janardhan Rao Doppa, John Walker Orr, Prashanth Mannem, Xiaoli Z. Fern, Thomas G. Dietterich, Prasad Tadepalli
2014	J	`jnl`	Reconstructing Velocities of Migrating Birds from Weather Radar - A Case Study in Computational Sustainability. AI Mag. Andrew Farnsworth, Daniel Sheldon, Jeffrey Geevarghese, Jed Irvine, Benjamin Van Doren, Kevin F. Webb, Thomas G. Dietterich, Steve Kelling
2013	A*	`conf`	Approximate Bayesian Inference for Reconstructing Velocities of Migrating Birds from Weather Radar. AAAI Daniel Sheldon, Andrew Farnsworth, Jed Irvine, Benjamin Van Doren, Kevin F. Webb, Thomas G. Dietterich, Steve Kelling
2013	—	`conf`	Approximate Inference in Collective Graphical Models. ICML (3) Daniel Sheldon, Tao Sun, Akshat Kumar, Thomas G. Dietterich
2013	A*	`conf`	Detecting insider threats in a real corporate database of computer usage activity. KDD Ted E. Senator, Henry G. Goldberg, Alex Memory, William T. Young, Brad Rees, Robert Pierce, Daniel Huang, Matthew Reardon, David A. Bader, Edmond Chow, Irfan A. Essa, Joshua Jones, Vinay Bettadapura, Duen Horng Chau, Oded Green, Oguz Kaya, Anita Zakrzewska, Erica Briscoe, Rudolph L. Mappus IV, Robert McColl, Lora Weiss, Thomas G. Dietterich, Alan Fern, Weng-Keen Wong, Shubhomoy Das, Andrew Emmott, Jed Irvine, Jay Yoon Lee, Danai Koutra, Christos Faloutsos, Daniel D. Corkill, Lisa Friedland, Amanda Gentzel, David D. Jensen
2013	A*	`conf`	Guiding Scientific Discovery with Explanations Using DEMUD. AAAI Kiri L. Wagstaff, Nina L. Lanza, David R. Thompson, Thomas G. Dietterich, Martha S. Gilmore
2013	—	`conf`	Learning to Detect Basal Tubules of Nematocysts in SEM Images. ICCV Workshops Michael Lam, Janardhan Rao Doppa, Xu Hu, Sinisa Todorovic, Thomas G. Dietterich, Abigail Reft, Marymegan Daly
2013	A*	`conf`	PAC Optimal Planning for Invasive Species Management: Improved Exploration for Reinforcement Learning from Simulator-Defined MDPs. AAAI Thomas G. Dietterich, Majid Alkaee Taleghan, Mark Crowley
2013	—	`conf`	Zero-Shot Learning and Detection of Teeth in Images of Bat Skulls. ICCV Workshops Xu Hu, Michael Lam, Sinisa Todorovic, Thomas G. Dietterich, Maureen A. OLeary, Andrea L. Cirranello, Nancy B. Simmons, Paúl M. Velazco
2012	—	`conf`	A Conditional Multinomial Mixture Model for Superset Label Learning. NIPS Li-Ping Liu, Thomas G. Dietterich
2012	J	`jnl`	Active Imitation Learning via Reduction to I.I.D. Active Learning CoRR Kshitij Judah, Alan Fern, Thomas G. Dietterich
2012	A	`conf`	Active Imitation Learning via Reduction to I.I.D. Active Learning. UAI Kshitij Judah, Alan Fern, Thomas G. Dietterich
2012	J	`jnl`	An Ensemble Architecture for Learning Complex Problem-Solving Techniques from Demonstration. ACM Trans. Intell. Syst. Technol. Xiaoqin Zhang, Bhavesh Shrestha, Sung Wook Yoon, Subbarao Kambhampati, Phillip DiBona, Jinhong K. Guo, Daniel McFarlane, Martin O. Hofmann, Kenneth R. Whitebread, Darren Scott Appling, Elizabeth T. Whitaker, Ethan Trewhitt, Li Ding, James Michaelis, Deborah L. McGuinness, James A. Hendler, Janardhan Rao Doppa, Charles Parker, Thomas G. Dietterich, Prasad Tadepalli, Weng-Keen Wong, Derek T. Green, Antons Rebguns, Diana F. Spears, Ugur Kuter, Geoffrey Levine, Gerald DeJong, Reid MacTavish, Santiago Ontañón, Jainarayan Radhakrishnan, Ashwin Ram, Hala Mostafa, Huzaifa Zafar, Chongjie Zhang, Daniel D. Corkill, Victor R. Lesser, Zhexuan Song
2012	J	`jnl`	Inferring Strategies from Limited Reconnaissance in Real-time Strategy Games CoRR Jesse Hostetler, Ethan W. Dereszynski, Thomas G. Dietterich, Alan Fern
2012	A	`conf`	Inferring Strategies from Limited Reconnaissance in Real-time Strategy Games. UAI Jesse Hostetler, Ethan W. Dereszynski, Thomas G. Dietterich, Alan Fern
2012	J	`jnl`	Learning from Sparse Data by Exploiting Monotonicity Constraints CoRR Eric Altendorf, Angelo C. Restificar, Thomas G. Dietterich
2012	—	`conf`	Machine learning for computational sustainability. IGCC Thomas G. Dietterich, Ethan W. Dereszynski, Rebecca A. Hutchinson, Dan Sheldon
2012	J	`jnl`	Probabilistic Models for Anomaly Detection in Remote Sensor Data Streams CoRR Ethan W. Dereszynski, Thomas G. Dietterich
2011	J	`jnl`	Automatic Discovery and Transfer of Task Hierarchies in Reinforcement Learning. AI Mag. Neville Mehta, Soumya Ray, Prasad Tadepalli, Thomas G. Dietterich
2011	—	`conf`	Collective Graphical Models. NIPS Daniel Sheldon, Thomas G. Dietterich
2011	J	`jnl`	FolderPredictor: Reducing the cost of reaching the right folder. ACM Trans. Intell. Syst. Technol. Xinlong Bao, Thomas G. Dietterich
2011	A*	`conf`	Incorporating Boosted Regression Trees into Ecological Latent Variable Models. AAAI Rebecca A. Hutchinson, Li-Ping Liu, Thomas G. Dietterich
2011	J	`jnl`	Integrating Learning from Examples into the Search for Diagnostic Policies CoRR Valentina Bayer Zubek, Thomas G. Dietterich
2011	—	`conf`	Inverting Grice's Maxims to Learn Rules from Natural Language Extractions. NIPS Shahed Sorower, Thomas G. Dietterich, Janardhan Rao Doppa, John Walker Orr, Prasad Tadepalli, Xiaoli Z. Fern
2011	—	`conf`	Learning Probabilistic Behavior Models in Real-Time Strategy Games. AIIDE Ethan W. Dereszynski, Jesse Hostetler, Alan Fern, Thomas G. Dietterich, Thao-Trang Hoang, Mark Udarbe
2011	C	`conf`	Learning Rules from Incomplete Examples via Implicit Mention Models. ACML Janardhan Rao Doppa, Shahed Sorower, Mohammad NasrEsfahani, John Walker Orr, Thomas G. Dietterich, Xiaoli Z. Fern, Prasad Tadepalli, Jed Irvine
2011	J	`jnl`	Spatiotemporal Models for Data-Anomaly Detection in Dynamic Environmental Monitoring Campaigns. ACM Trans. Sens. Networks Ethan W. Dereszynski, Thomas G. Dietterich
2011	A	`conf`	Stacked spatial-pyramid kernel: An object-class recognition method to combine scores from random trees. WACV Natalia Larios Delgado, Junyuan Lin, Mengzi Zhang, David A. Lytle, Andrew Moldenke, Linda G. Shapiro, Thomas G. Dietterich
2010	—	`ch.`	Cyber SA: Situational Awareness for Cyber Defense. Cyber Situational Awareness Paul Barford, Marc Dacier, Thomas G. Dietterich, Matt Fredrikson, Jonathon T. Giffin, Sushil Jajodia, Somesh Jha, Jason H. Li, Peng Liu, Peng Ning, Xinming Ou, Dawn Song, Laura Strater, Vipin Swarup, George P. Tadda, C. Wang, John Yen
2010	B	`conf`	Haar Random Forest Features and SVM Spatial Matching Kernel for Stonefly Species Identification. ICPR Natalia Larios, Bilge Soran, Linda G. Shapiro, Gonzalo Martínez-Muñoz, Junyuan Lin, Thomas G. Dietterich
2010	—	`ch.`	Machine Learning Methods for High Level Cyber Situation Awareness. Cyber Situational Awareness Thomas G. Dietterich, Xinlong Bao, Victoria Keiser, Jianqiang Shen
2010	A*	`conf`	Reinforcement Learning Via Practice and Critique Advice. AAAI Kshitij Judah, Saikat Roy, Alan Fern, Thomas G. Dietterich
2010	A*	`conf`	The life and times of files and information: a study of desktop provenance. CHI Carlos Jensen, Heather Lonsdale, Eleanor Wynn, Jill Cao, Michael Slater, Thomas G. Dietterich
2009	A	`conf`	A Family of Large Margin Linear Classifiers and Its Application in Dynamic Environments. SDM Jianqiang Shen, Thomas G. Dietterich
2009	J	`jnl`	A family of large margin linear classifiers and its application in dynamic environments. Stat. Anal. Data Min. Jianqiang Shen, Thomas G. Dietterich
2009	C	`conf`	An Ensemble Learning and Problem Solving Architecture for Airspace Management. IAAI Xiaoqin Zhang, Sung Wook Yoon, Phillip DiBona, Darren Scott Appling, Li Ding, Janardhan Rao Doppa, Derek T. Green, Jinhong K. Guo, Ugur Kuter, Geoffrey Levine, Reid MacTavish, Daniel McFarlane, James Michaelis, Hala Mostafa, Santiago Ontañón, Charles Parker, Jainarayan Radhakrishnan, Antons Rebguns, Bhavesh Shrestha, Zhexuan Song, Ethan Trewhitt, Huzaifa Zafar, Chongjie Zhang, Daniel D. Corkill, Gerald DeJong, Thomas G. Dietterich, Subbarao Kambhampati, Victor R. Lesser, Deborah L. McGuinness, Ashwin Ram, Diana F. Spears, Prasad Tadepalli, Elizabeth T. Whitaker, Weng-Keen Wong, James A. Hendler, Martin O. Hofmann, Kenneth R. Whitebread
2009	A	`conf`	Detecting and correcting user activity switches: algorithms and interfaces. IUI Jianqiang Shen, Jed Irvine, Xinlong Bao, Michael Goodman, Stephen Kolibaba, Anh Tran, Fredric Carl, Brenton Kirschner, Simone Stumpf, Thomas G. Dietterich
2009	A*	`conf`	Dictionary-free categorization of very similar objects via stacked evidence trees. CVPR Gonzalo Martínez-Muñoz, Natalia Larios Delgado, Eric N. Mortensen, Wei Zhang, Asako Yamamuro, Robert Paasch, Nadia Payet, David A. Lytle, Linda G. Shapiro, Sinisa Todorovic, Andrew Moldenke, Thomas G. Dietterich
2009	A	`conf`	Discovering frequent work procedures from resource connections. IUI Jianqiang Shen, Erin Fitzhenry, Thomas G. Dietterich
2009	J	`jnl`	Interacting meaningfully with machine learning systems: Three experiments. Int. J. Hum. Comput. Stud. Simone Stumpf, Vidya Rajaram, Lida Li, Weng-Keen Wong, Margaret M. Burnett, Thomas G. Dietterich, Erin Sullivan, Jonathan L. Herlocker
2009	A*	`conf`	Learning non-redundant codebooks for classifying complex objects. ICML Wei Zhang, Akshat Surve, Xiaoli Z. Fern, Thomas G. Dietterich
2009	C	`conf`	Machine Learning and Ecosystem Informatics: Challenges and Opportunities. ACML Thomas G. Dietterich
2009	A*	`conf`	Machine Learning in Ecosystem Informatics and Sustainability. IJCAI Thomas G. Dietterich
2008	J	`jnl`	Automated insect identification through concatenated histograms of local appearance features: feature vector generation and region detection for deformable objects. Mach. Vis. Appl. Natalia Larios, Hongli Deng, Wei Zhang, Matt Sarpola, Jenny Yuen, Robert Paasch, Andrew Moldenke, David A. Lytle, Salvador Ruiz-Correa, Eric N. Mortensen, Linda G. Shapiro, Thomas G. Dietterich
2008	A*	`conf`	Automatic discovery and transfer of MAXQ hierarchies. ICML Neville Mehta, Soumya Ray, Prasad Tadepalli, Thomas G. Dietterich
2008	A*	`conf`	Integrating Multiple Learning Components through Markov Logic. AAAI Thomas G. Dietterich, Xinlong Bao
2008	—	`conf`	Learning MDP Action Models Via Discrete Mixture Trees. ECML/PKDD (2) Michael Wynkoop, Thomas G. Dietterich
2008	J	`jnl`	Learning first-order probabilistic models with combining rules. Ann. Math. Artif. Intell. Sriraam Natarajan, Prasad Tadepalli, Thomas G. Dietterich, Alan Fern
2008	B	`conf`	Learning visual dictionaries and decision lists for object recognition. ICPR Wei Zhang, Thomas G. Dietterich
2008	—	`ed.`	Probabilistic, Logical and Relational Learning - A Further Synthesis, 15.04. - 20.04.2007 Probabilistic, Logical and Relational Learning - A Further Synthesis Luc De Raedt, Thomas G. Dietterich, Lise Getoor, Kristian Kersting, Stephen H. Muggleton
2008	J	`jnl`	Structured machine learning: the next ten years. Mach. Learn. Thomas G. Dietterich, Pedro M. Domingos, Lise Getoor, Stephen H. Muggleton, Prasad Tadepalli
2007	—	`conf`	07161 Abstracts Collection -- Probabilistic, Logical and Relational Learning - A Further Synthesis. Probabilistic, Logical and Relational Learning - A Further Synthesis Luc De Raedt, Thomas G. Dietterich, Lise Getoor, Kristian Kersting, Stephen H. Muggleton
2007	J	`jnl`	AAAI-07 Workshop Reports. AI Mag. Sarabjot Singh Anand, Daniel Bahls, Catherina Burghart, Mark H. Burstein, Huajun Chen, John Collins, Thomas G. Dietterich, Jon Doyle, Chris Drummond, William Elazmeh, Christopher W. Geib, Judy Goldsmith, Hans W. Guesgen, Jim Hendler, Dietmar Jannach, Nathalie Japkowicz, Ulrich Junker, Gal A. Kaminka, Alfred Kobsa, Jérôme Lang, David B. Leake, Lundy Lewis, Gerard Ligozat, Sofus A. Macskassy, Drew V. McDermott, Ted Metzler, Bamshad Mobasher, Ullas Nambiar, Zaiqing Nie, Klas Orsvärn, Barry O'Sullivan, David V. Pynadath, Jochen Renz, Rita V. Rodríguez, Thomas Roth-Berghofer, Stefan Schulz, Rudi Studer, Yimin Wang, Michael P. Wellman
2007	A	`conf`	Active EM to reduce noise in activity recognition. IUI Jianqiang Shen, Thomas G. Dietterich
2007	A	`conf`	Automated Insect Identification through Concatenated Histograms of Local Appearance Features. WACV Natalia Larios, Hongli Deng, Wei Zhang, Matt Sarpola, Jenny Yuen, Robert Paasch, Andrew Moldenke, David A. Lytle, Ruiz Correa, Eric N. Mortensen, Linda G. Shapiro, Thomas G. Dietterich
2007	—	`conf`	Improving Intelligent Assistants for Desktop Activities. AAAI Spring Symposium: Interaction Challenges for Intelligent Assistants Simone Stumpf, Margaret M. Burnett, Thomas G. Dietterich
2007	—	`conf`	Improving Intelligent Assistants for Desktop Activities. Interaction Challenges for Intelligent Assistants Simone Stumpf, Margaret M. Burnett, Thomas G. Dietterich
2007	B	`conf`	Machine Learning in Ecosystem Informatics. ALT Thomas G. Dietterich
2007	B	`conf`	Machine Learning in Ecosystem Informatics. Discovery Science Thomas G. Dietterich
2007	A*	`conf`	Principal Curvature-Based Region Detector for Object Recognition. CVPR Hongli Deng, Wei Zhang, Eric N. Mortensen, Thomas G. Dietterich, Linda G. Shapiro
2007	A	`conf`	Probabilistic Models for Anomaly Detection in Remote Sensor Data Streams. UAI Ethan W. Dereszynski, Thomas G. Dietterich
2007	A*	`conf`	Real-Time Detection of Task Switches of Desktop Users. IJCAI Jianqiang Shen, Lida Li, Thomas G. Dietterich
2007	A	`conf`	Toward harnessing user feedback for machine learning. IUI Simone Stumpf, Vidya Rajaram, Lida Li, Margaret M. Burnett, Thomas G. Dietterich, Erin Sullivan, Russell Drummond, Jonathan L. Herlocker
2006	—	`conf`	A Hierarchical Object Recognition System Based on Multi-scale Principal Curvature Regions. ICPR (1) Wei Zhang, Hongli Deng, Thomas G. Dietterich, Eric N. Mortensen
2006	A	`conf`	A hybrid learning system for recognizing user tasks from desktop activities and email messages. IUI Jianqiang Shen, Lida Li, Thomas G. Dietterich, Jonathan L. Herlocker
2006	A	`conf`	Fewer clicks and less frustration: reducing the cost of reaching the right folder. IUI Xinlong Bao, Jonathan L. Herlocker, Thomas G. Dietterich
2006	—	`ed.`	Probabilistic, Logical and Relational Learning - Towards a Synthesis, 30. January - 4. February 2005 Probabilistic, Logical and Relational Learning Luc De Raedt, Thomas G. Dietterich, Lise Getoor, Stephen H. Muggleton
2006	—	`conf`	Reinforcement Matching Using Region Context. CVPR Workshops Hongli Deng, Eric N. Mortensen, Linda G. Shapiro, Thomas G. Dietterich
2005	—	`conf`	05051 Abstracts Collection - Probabilistic, Logical and Relational Learning - Towards a Synthesis. Probabilistic, Logical and Relational Learning Luc De Raedt, Thomas G. Dietterich, Lise Getoor, Stephen H. Muggleton
2005	—	`conf`	05051 Executive Summary - Probabilistic, Logical and Relational Learning - Towards a Synthesis. Probabilistic, Logical and Relational Learning Luc De Raedt, Thomas G. Dietterich, Lise Getoor, Stephen H. Muggleton
2005	J	`jnl`	Integrating Learning from Examples into the Search for Diagnostic Policies. J. Artif. Intell. Res. Valentina Bayer Zubek, Thomas G. Dietterich
2005	A*	`conf`	Learning first-order probabilistic models with combining rules. ICML Sriraam Natarajan, Prasad Tadepalli, Eric Altendorf, Thomas G. Dietterich, Alan Fern, Angelo C. Restificar
2005	A	`conf`	Learning from Sparse Data by Exploiting Monotonicity Constraints. UAI Eric Altendorf, Angelo C. Restificar, Thomas G. Dietterich
2005	A	`conf`	TaskTracer: a desktop environment to support multi-tasking knowledge workers. IUI Anton N. Dragunov, Thomas G. Dietterich, Kevin Johnsrude, Matthew R. McLaughlin, Lida Li, Jonathan L. Herlocker
2005	A*	`conf`	The TaskTracker System. AAAI Simone Stumpf, Xinlong Bao, Anton N. Dragunov, Thomas G. Dietterich, Jonathan L. Herlocker, Kevin Johnsrude, Lida Li, Jianqiang Shen
2004	J	`jnl`	Bias-Variance Analysis of Support Vector Machines for the Development of SVM-Based Ensemble Methods. J. Mach. Learn. Res. Giorgio Valentini, Thomas G. Dietterich
2004	A*	`conf`	Improving SVM accuracy by training on auxiliary data sources. ICML Pengcheng Wu, Thomas G. Dietterich
2004	A*	`conf`	Training conditional random fields via gradient tree boosting. ICML Thomas G. Dietterich, Adam Ashenfelter, Yaroslav Bulatov
2003	A*	`conf`	Low Bias Bagged Support Vector Machines. ICML Giorgio Valentini, Thomas G. Dietterich
2003	A*	`conf`	Model-based Policy Gradient Reinforcement Learning. ICML Xin Wang, Thomas G. Dietterich
2002	—	`conf`	A Multi-agent Architecture Integrating Learning and Fuzzy Techniques for Landmark-Based Robot Navigation. CCIA Dídac Busquets, Ramón López de Mántaras, Carles Sierra, Thomas G. Dietterich
2002	A*	`conf`	Action Refinement in Reinforcement Learning by Probability Smoothing. ICML Thomas G. Dietterich, Dídac Busquets, Ramón López de Mántaras, Carles Sierra
2002	—	`conf`	Bias-Variance Analysis and Ensembles of SVM. Multiple Classifier Systems Giorgio Valentini, Thomas G. Dietterich
2002	—	`conf`	Machine Learning for Sequential Data: A Review. SSPR/SPR Thomas G. Dietterich
2002	A*	`conf`	Pruning Improves Heuristic Search for Cost-Sensitive Learning. ICML Valentina Bayer Zubek, Thomas G. Dietterich
2001	—	`ed.`	Advances in Neural Information Processing Systems 13, Papers from Neural Information Processing Systems (NIPS) 2000, Denver, CO, USA NIPS Todd K. Leen, Thomas G. Dietterich, Volker Tresp
2001	—	`ed.`	Advances in Neural Information Processing Systems 14 [Neural Information Processing Systems: Natural and Synthetic, NIPS 2001, December 3-8, 2001, Vancouver, British Columbia, Canada] NIPS Thomas G. Dietterich, Suzanna Becker, Zoubin Ghahramani
2001	—	`conf`	Batch Value Function Approximation via Support Vectors. NIPS Thomas G. Dietterich, Xin Wang
2001	—	`conf`	Stabilizing Value Function Approximation with the BFBP Algorithm. NIPS Xin Wang, Thomas G. Dietterich
2001	—	`conf`	Support Vectors for Reinforcement Learning. ECML Thomas G. Dietterich, Xin Wang
2001	—	`conf`	Support Vectors for Reinforcement Learning. PKDD Thomas G. Dietterich, Xin Wang
2000	A*	`conf`	A Divide and Conquer Approach to Learning from Prior Knowledge. ICML Eric Chown, Thomas G. Dietterich
2000	B	`conf`	A POMDP Approximation Algorithm That Anticipates the Need to Observe. PRICAI Valentina Bayer Zubek, Thomas G. Dietterich
2000	J	`jnl`	An Experimental Comparison of Three Methods for Constructing Ensembles of Decision Trees: Bagging, Boosting, and Randomization. Mach. Learn. Thomas G. Dietterich
2000	—	`conf`	An Overview of MAXQ Hierarchical Reinforcement Learning. SARA Thomas G. Dietterich
2000	A*	`conf`	Bootstrap Methods for the Cost-Sensitive Evaluation of Classifiers. ICML Dragos D. Margineantu, Thomas G. Dietterich
2000	—	`conf`	Ensemble Methods in Machine Learning. Multiple Classifier Systems Thomas G. Dietterich
2000	J	`jnl`	Hierarchical Reinforcement Learning with the MAXQ Value Function Decomposition. J. Artif. Intell. Res. Thomas G. Dietterich
2000	A*	`conf`	Mining IC test data to optimize VLSI testing. KDD Tony Fountain, Thomas G. Dietterich, Bill Sudyka
2000	B	`conf`	The Divide-and-Conquer Manifesto. ALT Thomas G. Dietterich
1999	J	`jnl`	Hierarchical Reinforcement Learning with the MAXQ Value Function Decomposition CoRR Thomas G. Dietterich
1999	J	`jnl`	State Abstraction in MAXQ Hierarchical Reinforcement Learning CoRR Thomas G. Dietterich
1999	—	`conf`	State Abstraction in MAXQ Hierarchical Reinforcement Learning. NIPS Thomas G. Dietterich
1998	J	`jnl`	Approximate Statistical Tests for Comparing Supervised Classification Learning Algorithms. Neural Comput. Thomas G. Dietterich
1998	A*	`conf`	The MAXQ Method for Hierarchical Reinforcement Learning. ICML Thomas G. Dietterich
1997	J	`jnl`	Explanation-Based Learning and Reinforcement Learning: A Unified View. Mach. Learn. Thomas G. Dietterich, Nicholas S. Flann
1997	A*	`conf`	Hierarchical Explanation-Based Reinforcement Learning. ICML Prasad Tadepalli, Thomas G. Dietterich
1997	J	`jnl`	Machine-Learning Research. AI Mag. Thomas G. Dietterich
1997	A*	`conf`	Pruning Adaptive Boosting. ICML Dragos D. Margineantu, Thomas G. Dietterich
1997	J	`jnl`	Solving the Multiple Instance Problem with Axis-Parallel Rectangles. Artif. Intell. Thomas G. Dietterich, Richard H. Lathrop, Tomás Lozano-Pérez
1996	A*	`conf`	Applying the Waek Learning Framework to Understand and Improve C4.5. ICML Thomas G. Dietterich, Michael J. Kearns, Yishay Mansour
1996	J	`jnl`	Editorial. Mach. Learn. Thomas G. Dietterich
1996	J	`jnl`	Machine Learning. ACM Comput. Surv. Thomas G. Dietterich
1995	J	`jnl`	A Comparison of ID3 and Backpropagation for English Text-to-Speech Mapping. Mach. Learn. Thomas G. Dietterich, Hermann Hild, Ghulum Bakiri
1995	A*	`conf`	A Reinforcement Learning Approach to job-shop Scheduling. IJCAI Wei Zhang, Thomas G. Dietterich
1995	J	`jnl`	An Experimental Comparison of the Nearest-Neighbor and Nearest-Hyperrectangle Algorithms. Mach. Learn. Dietrich Wettschereck, Thomas G. Dietterich
1995	A*	`conf`	Error-Correcting Output Coding Corrects Bias and Variance. ICML Eun Bae Kong, Thomas G. Dietterich
1995	A*	`conf`	Explanation-Based Learning and Reinforcement Learning: A Unified View. ICML Thomas G. Dietterich, Nicholas S. Flann
1995	—	`conf`	High-Performance Job-Shop Scheduling With A Time-Delay TD-lambda Network. NIPS Wei Zhang, Thomas G. Dietterich
1995	J	`jnl`	Overfitting and Undercomputing in Machine Learning. ACM Comput. Surv. Thomas G. Dietterich
1995	J	`jnl`	Solving Multiclass Learning Problems via Error-Correcting Output Codes CoRR Thomas G. Dietterich, Ghulum Bakiri
1995	J	`jnl`	Solving Multiclass Learning Problems via Error-Correcting Output Codes. J. Artif. Intell. Res. Thomas G. Dietterich, Ghulum Bakiri
1994	J	`jnl`	Compass: A shape-based machine learning tool for drug design. J. Comput. Aided Mol. Des. Ajay N. Jain, Thomas G. Dietterich, Richard H. Lathrop, David Chapman, Roger E. Critchlow Jr., Barr E. Bauer, Teresa A. Webster, Tomás Lozano-Pérez
1994	J	`jnl`	Editorial: New Editorial Board Members. Mach. Learn. Thomas G. Dietterich
1994	J	`jnl`	Learning Boolean Concepts in the Presence of Many Irrelevant Features. Artif. Intell. Hussein Almuallim, Thomas G. Dietterich
1993	—	`conf`	A Comparison of Dynamic Reposing and Tangent Distance for Drug Activity Prediction. NIPS Thomas G. Dietterich, Ajay N. Jain, Richard H. Lathrop, Tomás Lozano-Pérez
1993	J	`jnl`	Editorial. Mach. Learn. Thomas G. Dietterich
1993	—	`conf`	Locally Adaptive Nearest Neighbor Algorithms. NIPS Dietrich Wettschereck, Thomas G. Dietterich
1993	—	`conf`	Memory-Based Methods for Regression and Classification. NIPS Thomas G. Dietterich, Dietrich Wettschereck, Christopher G. Atkeson, Andrew W. Moore
1992	J	`jnl`	Editorial. Mach. Learn. Thomas G. Dietterich
1992	—	`conf`	On Learning More Concepts. ML Hussein Almuallim, Thomas G. Dietterich
1991	A*	`conf`	Error-Correcting Output Codes: A General Method for Improving Multiclass Inductive Learning Programs. AAAI Thomas G. Dietterich, Ghulum Bakiri
1991	—	`conf`	Improving the Performance of Radial Basis Function Networks by Learning Center Locations. NIPS Dietrich Wettschereck, Thomas G. Dietterich
1991	—	`conf`	Knowledge Compilation to Speed Up Numerical Optimisation. AI*IA Giuseppe Cerbone, Thomas G. Dietterich
1991	—	`conf`	Knowledge Compilation to Speed Up Numerical Optimization. ML Giuseppe Cerbone, Thomas G. Dietterich
1991	J	`jnl`	Knowledge Compilation: A Symposium. IEEE Expert Ashok K. Goel, Tom Bylander, B. Chandrasekaran, Thomas G. Dietterich, Richard M. Keller, Chris Tong
1991	A*	`conf`	Learning with Many Irrelevant Features. AAAI Hussein Almuallim, Thomas G. Dietterich
1991	—	`conf`	Machine Learning in Engineering Automation. ML Steve A. Chien, Bradley L. Whitehall, Thomas G. Dietterich, Richard J. Doyle, Brian Falkenhainer, James Garrett, Stephen C. Y. Lu
1990	—	`conf`	A Comparative Study of ID3 and Backpropagation for English Text-to-Speech Mapping. ML Thomas G. Dietterich, Hermann Hild, Ghulum Bakiri
1990	J	`jnl`	Exploratory Research in Machine Learning. Mach. Learn. Thomas G. Dietterich
1990	A*	`ed.`	Proceedings of the 8th National Conference on Artificial Intelligence. Boston, Massachusetts, USA, July 29 - August 3, 1990, 2 Volumes. AAAI Howard E. Shrobe, Thomas G. Dietterich, William R. Swartout
1989	J	`jnl`	A Study of Explanation-Based Methods for Inductive Learning. Mach. Learn. Nicholas S. Flann, Thomas G. Dietterich
1989	—	`conf`	Limitations on Inductive Learning. ML Thomas G. Dietterich
1989	J	`jnl`	News and Notes. Mach. Learn. Thomas G. Dietterich
1989	J	`jnl`	News and Notes. Mach. Learn. Thomas G. Dietterich
1989	—	`conf`	What Good Are Experiments?. ML Ritchey A. Ruff, Thomas G. Dietterich
1988	J	`jnl`	A model of the mechanical design process based on empirical data. Artif. Intell. Eng. Des. Anal. Manuf. David G. Ullman, Thomas G. Dietterich, Larry A. Stauffer
1988	A*	`conf`	An Efficient ATMS for Equivalence Relations. AAAI Caroline N. Koff, Nicholas S. Flann, Thomas G. Dietterich
1988	J	`jnl`	News and Notes. Mach. Learn. Thomas G. Dietterich
1987	A*	`conf`	Forward Chaining Logic Programming with the ATMS. AAAI Nicholas S. Flann, Thomas G. Dietterich, Dan R. Corpon
1987	J	`jnl`	News and Notes. Mach. Learn. Thomas G. Dietterich
1987	J	`jnl`	News and Notes. Mach. Learn. Thomas G. Dietterich
1987	J	`jnl`	News and Notes. Mach. Learn. Thomas G. Dietterich
1987	J	`jnl`	News and Notes. Mach. Learn. Thomas G. Dietterich
1986	J	`jnl`	Learning at the Knowledge Level. Mach. Learn. Thomas G. Dietterich
1986	J	`jnl`	News and Notes. Mach. Learn. Thomas G. Dietterich
1986	J	`jnl`	News and Notes. Mach. Learn. Thomas G. Dietterich, Nicholas S. Flann, David C. Wilkins
1986	J	`jnl`	News and Notes. Mach. Learn. Yves Kodratoff, Gheorghe Tecuci, Thomas G. Dietterich
1986	A*	`conf`	Selecting Appropriate Representations for Learning from Examples. AAAI Nicholas S. Flann, Thomas G. Dietterich
1985	J	`jnl`	Discovering Patterns in Sequences of Events. Artif. Intell. Thomas G. Dietterich, Ryszard S. Michalski
1984	A*	`conf`	Learning About Systems That Contain State Variables. AAAI Thomas G. Dietterich
1981	J	`jnl`	Inductive Learning of Structural Descriptions: Evaluation Criteria and Comparative Review of Selected Methods. Artif. Intell. Thomas G. Dietterich, Ryszard S. Michalski
1980	A*	`conf`	Applying General Induction Methods to the Card Game Eleusis. AAAI Thomas G. Dietterich
1979	A*	`conf`	Learning and Generalization of Characteristic Descriptions: Evaluation Criteria and Comparative Review of Selected Methods. IJCAI Thomas G. Dietterich, Ryszard S. Michalski