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Thomas G. Dietterich
Thomas Glenn Dietterich
Author information
- affiliation: Oregon State University, School of Electrical Engineering and Computer Science
2010 – today
- 2013
[c95]Thomas G. Dietterich, Majid Alkaee Taleghan, Mark Crowley: PAC Optimal Planning for Invasive Species Management: Improved Exploration for Reinforcement Learning from Simulator-Defined MDPs. AAAI 2013- [c94]Daniel R. Sheldon, Andrew Farnsworth, Jed Irvine, Benjamin Van Doren, Kevin F. Webb, Thomas G. Dietterich, Steve Kelling: Approximate Bayesian Inference for Reconstructing Velocities of Migrating Birds from Weather Radar. AAAI 2013
- [c93]Kiri L. Wagstaff, Nina L. Lanza, David R. Thompson, Thomas G. Dietterich, Martha S. Gilmore: Guiding Scientific Discovery with Explanations Using DEMUD. AAAI 2013
- [c92]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 Jensen: Detecting insider threats in a real corporate database of computer usage activity. KDD 2013: 1393-1401
- 2012
- [j46]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: An Ensemble Architecture for Learning Complex Problem-Solving Techniques from Demonstration. ACM TIST 3(4): 75 (2012)
- [c91]Kshitij Judah, Alan Paul Fern, Thomas Glenn Dietterich: Active Imitation Learning via Reduction to I.I.D. Active Learning. AAAI Fall Symposium: Robots Learning Interactively from Human Teachers 2012
- [c90]Thomas G. Dietterich, Ethan W. Dereszynski, Rebecca A. Hutchinson, Daniel R. Sheldon: Machine learning for computational sustainability. IGCC 2012: 1
- [c89]Li-Ping Liu, Thomas G. Dietterich: A Conditional Multinomial Mixture Model for Superset Label Learning. NIPS 2012: 557-565
- [c88]Jesse Hostetler, Ethan W. Dereszynski, Thomas G. Dietterich, Alan Fern: Inferring Strategies from Limited Reconnaissance in Real-time Strategy Games. UAI 2012: 367-376
- [c87]Kshitij Judah, Alan Fern, Thomas G. Dietterich: Active Imitation Learning via Reduction to I.I.D. Active Learning. UAI 2012: 428-437
- [i8]Ethan W. Dereszynski, Thomas G. Dietterich: Probabilistic Models for Anomaly Detection in Remote Sensor Data Streams. CoRR abs/1206.5250 (2012)
- [i7]Eric Altendorf, Angelo C. Restificar, Thomas G. Dietterich: Learning from Sparse Data by Exploiting Monotonicity Constraints. CoRR abs/1207.1364 (2012)
- [i6]Kshitij Judah, Alan Fern, Thomas G. Dietterich: Active Imitation Learning via Reduction to I.I.D. Active Learning. CoRR abs/1210.4876 (2012)
- [i5]Jesse Hostetler, Ethan W. Dereszynski, Thomas G. Dietterich, Alan Fern: Inferring Strategies from Limited Reconnaissance in Real-time Strategy Games. CoRR abs/1210.4880 (2012)
- 2011
- [j45]Neville Mehta, Soumya Ray, Prasad Tadepalli, Thomas G. Dietterich: Automatic Discovery and Transfer of Task Hierarchies in Reinforcement Learning. AI Magazine 32(1): 35-50 (2011)
- [j44]Janardhan Rao Doppa, Shahed Sorower, Mohammad NasrEsfahani, Walker Orr, Thomas G. Dietterich, Xiaoli Fern, Prasad Tadepalli, Jed Irvine: Learning Rules from Incomplete Examples via Implicit Mention Models. Journal of Machine Learning Research - Proceedings Track 20: 197-212 (2011)
- [j43]Xinlong Bao, Thomas G. Dietterich: FolderPredictor: Reducing the cost of reaching the right folder. ACM TIST 2(1): 8 (2011)
- [j42]Ethan W. Dereszynski, Thomas G. Dietterich: Spatiotemporal Models for Data-Anomaly Detection in Dynamic Environmental Monitoring Campaigns. TOSN 8(1): 3 (2011)
- [c86]Rebecca A. Hutchinson, Li-Ping Liu, Thomas G. Dietterich: Incorporating Boosted Regression Trees into Ecological Latent Variable Models. AAAI 2011
- [c85]Ethan W. Dereszynski, Jesse Hostetler, Alan Fern, Thomas G. Dietterich, Thao-Trang Hoang, Mark Udarbe: Learning Probabilistic Behavior Models in Real-Time Strategy Games. AIIDE 2011
- [c84]Shahed Sorower, Thomas G. Dietterich, Janardhan Rao Doppa, Walker Orr, Prasad Tadepalli, Xiaoli Fern: Inverting Grice's Maxims to Learn Rules from Natural Language Extractions. NIPS 2011: 1053-1061
- [c83]
- [i4]Valentina Bayer Zubek, Thomas G. Dietterich: Integrating Learning from Examples into the Search for Diagnostic Policies. CoRR abs/1109.2127 (2011)
- 2010
- [c82]Kshitij Judah, Saikat Roy, Alan Fern, Thomas G. Dietterich: Reinforcement Learning Via Practice and Critique Advice. AAAI 2010
- [c81]Carlos Jensen, Heather Lonsdale, Eleanor Wynn, Jill Cao, Michael Slater, Thomas G. Dietterich: The life and times of files and information: a study of desktop provenance. CHI 2010: 767-776
- [c80]Natalia Larios, Bilge Soran, Linda G. Shapiro, Gonzalo Martínez-Muñoz, Junyuan Lin, Thomas G. Dietterich: Haar Random Forest Features and SVM Spatial Matching Kernel for Stonefly Species Identification. ICPR 2010: 2624-2627
- [p2]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: Cyber SA: Situational Awareness for Cyber Defense. Cyber Situational Awareness 2010: 3-13
- [p1]Thomas G. Dietterich, Xinlong Bao, Victoria Keiser, Jianqiang Shen: Machine Learning Methods for High Level Cyber Situation Awareness. Cyber Situational Awareness 2010: 227-247
2000 – 2009
- 2009
- [j41]Simone Stumpf, Vidya Rajaram, Lida Li, Weng-Keen Wong, Margaret M. Burnett, Thomas G. Dietterich, Erin Sullivan, Jonathan L. Herlocker: Interacting meaningfully with machine learning systems: Three experiments. Int. J. Hum.-Comput. Stud. 67(8): 639-662 (2009)
- [j40]Jianqiang Shen, Thomas G. Dietterich: A family of large margin linear classifiers and its application in dynamic environments. Statistical Analysis and Data Mining 2(5-6): 328-345 (2009)
- [c79]Thomas G. Dietterich: Machine Learning and Ecosystem Informatics: Challenges and Opportunities. ACML 2009: 1-5
- [c78]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: Dictionary-free categorization of very similar objects via stacked evidence trees. CVPR 2009: 549-556
- [c77]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: An Ensemble Learning and Problem Solving Architecture for Airspace Management. IAAI 2009
- [c76]Wei Zhang, Akshat Surve, Xiaoli Fern, Thomas G. Dietterich: Learning non-redundant codebooks for classifying complex objects. ICML 2009: 156
- [c75]Thomas G. Dietterich: Machine Learning in Ecosystem Informatics and Sustainability. IJCAI 2009: 8-13
- [c74]Jianqiang Shen, Jed Irvine, Xinlong Bao, Michael Goodman, Stephen Kolibaba, Anh Tran, Fredric Carl, Brenton Kirschner, Simone Stumpf, Thomas G. Dietterich: Detecting and correcting user activity switches: algorithms and interfaces. IUI 2009: 117-126
- [c73]Jianqiang Shen, Erin Fitzhenry, Thomas G. Dietterich: Discovering frequent work procedures from resource connections. IUI 2009: 277-286
- [c72]Jianqiang Shen, Thomas G. Dietterich: A Family of Large Margin Linear Classifiers and Its Application in Dynamic Environments. SDM 2009: 164-172
- 2008
- [j39]Sriraam Natarajan, Prasad Tadepalli, Thomas G. Dietterich, Alan Fern: Learning first-order probabilistic models with combining rules. Ann. Math. Artif. Intell. 54(1-3): 223-256 (2008)
- [j38]Thomas G. Dietterich, Pedro Domingos, Lise Getoor, Stephen Muggleton, Prasad Tadepalli: Structured machine learning: the next ten years. Machine Learning 73(1): 3-23 (2008)
- [j37]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: Automated insect identification through concatenated histograms of local appearance features: feature vector generation and region detection for deformable objects. Mach. Vis. Appl. 19(2): 105-123 (2008)
- [c71]Thomas G. Dietterich, Xinlong Bao: Integrating Multiple Learning Components through Markov Logic. AAAI 2008: 622-627
- [c70]Neville Mehta, Soumya Ray, Prasad Tadepalli, Thomas G. Dietterich: Automatic discovery and transfer of MAXQ hierarchies. ICML 2008: 648-655
- [c69]
- [c68]Michael Wynkoop, Thomas G. Dietterich: Learning MDP Action Models Via Discrete Mixture Trees. ECML/PKDD (2) 2008: 597-612
- [e5]Luc De Raedt, Thomas G. Dietterich, Lise Getoor, Kristian Kersting, Stephen Muggleton (Eds.): Probabilistic, Logical and Relational Learning - A Further Synthesis, 15.04. - 20.04.2007. Dagstuhl Seminar Proceedings 07161, Internationales Begegnungs- und Forschungszentrum fuer Informatik (IBFI), Schloss Dagstuhl, Germany 2008
- 2007
- [j36]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: AAAI-07 Workshop Reports. AI Magazine 28(4): 119-128 (2007)
- [c67]
- [c66]Hongli Deng, Wei Zhang, Eric N. Mortensen, Thomas G. Dietterich, Linda G. Shapiro: Principal Curvature-Based Region Detector for Object Recognition. CVPR 2007
- [c65]Luc De Raedt, Thomas G. Dietterich, Lise Getoor, Kristian Kersting, Stephen Muggleton: 07161 Abstracts Collection -- Probabilistic, Logical and Relational Learning - A Further Synthesis. Probabilistic, Logical and Relational Learning - A Further Synthesis 2007
- [c64]
- [c63]Simone Stumpf, Margaret M. Burnett, Thomas G. Dietterich: Improving Intelligent Assistants for Desktop Activities. Interaction Challenges for Intelligent Assistants 2007: 119-121
- [c62]Jianqiang Shen, Lida Li, Thomas G. Dietterich: Real-Time Detection of Task Switches of Desktop Users. IJCAI 2007: 2868-2873
- [c61]Simone Stumpf, Vidya Rajaram, Lida Li, Margaret M. Burnett, Thomas G. Dietterich, Erin Sullivan, Russell Drummond, Jonathan L. Herlocker: Toward harnessing user feedback for machine learning. IUI 2007: 82-91
- [c60]Jianqiang Shen, Thomas G. Dietterich: Active EM to reduce noise in activity recognition. IUI 2007: 132-140
- [c59]Ethan W. Dereszynski, Thomas G. Dietterich: Probabilistic Models for Anomaly Detection in Remote Sensor Data Streams. UAI 2007: 75-82
- [c58]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: Automated Insect Identification through Concatenated Histograms of Local Appearance Features. WACV 2007: 26
- 2006
- [c57]Wei Zhang, Hongli Deng, Thomas G. Dietterich, Eric N. Mortensen: A Hierarchical Object Recognition System Based on Multi-scale Principal Curvature Regions. ICPR (1) 2006: 778-782
- [c56]Jianqiang Shen, Lida Li, Thomas G. Dietterich, Jonathan L. Herlocker: A hybrid learning system for recognizing user tasks from desktop activities and email messages. IUI 2006: 86-92
- [c55]Xinlong Bao, Jonathan L. Herlocker, Thomas G. Dietterich: Fewer clicks and less frustration: reducing the cost of reaching the right folder. IUI 2006: 178-185
- [e4]Luc De Raedt, Thomas G. Dietterich, Lise Getoor, Stephen Muggleton (Eds.): Probabilistic, Logical and Relational Learning - Towards a Synthesis, 30. January - 4. February 2005. Dagstuhl Seminar Proceedings 05051, Internationales Begegnungs- und Forschungszentrum für Informatik (IBFI), Schloss Dagstuhl, Germany 2006
- 2005
- [j35]Valentina Bayer Zubek, Thomas G. Dietterich: Integrating Learning from Examples into the Search for Diagnostic Policies. J. Artif. Intell. Res. (JAIR) 24: 263-303 (2005)
- [c54]Simone Stumpf, Xinlong Bao, Anton N. Dragunov, Thomas G. Dietterich, Jonathan L. Herlocker, Kevin Johnsrude, Lida Li, Jianqiang Shen: The TaskTracker System. AAAI 2005: 1712-1713
- [c53]Luc De Raedt, Thomas G. Dietterich, Lise Getoor, Stephen Muggleton: 05051 Executive Summary - Probabilistic, Logical and Relational Learning - Towards a Synthesis. Probabilistic, Logical and Relational Learning 2005
- [c52]Luc De Raedt, Thomas G. Dietterich, Lise Getoor, Stephen Muggleton: 05051 Abstracts Collection - Probabilistic, Logical and Relational Learning - Towards a Synthesis. Probabilistic, Logical and Relational Learning 2005
- [c51]Sriraam Natarajan, Prasad Tadepalli, Eric Altendorf, Thomas G. Dietterich, Alan Fern, Angelo C. Restificar: Learning first-order probabilistic models with combining rules. ICML 2005: 609-616
- [c50]Anton N. Dragunov, Thomas G. Dietterich, Kevin Johnsrude, Matthew R. McLaughlin, Lida Li, Jonathan L. Herlocker: TaskTracer: a desktop environment to support multi-tasking knowledge workers. IUI 2005: 75-82
- [c49]Eric Altendorf, Angelo C. Restificar, Thomas G. Dietterich: Learning from Sparse Data by Exploiting Monotonicity Constraints. UAI 2005: 18-26
- 2004
- [j34]Giorgio Valentini, Thomas G. Dietterich: Bias-Variance Analysis of Support Vector Machines for the Development of SVM-Based Ensemble Methods. Journal of Machine Learning Research 5: 725-775 (2004)
- [c48]Thomas G. Dietterich, Adam Ashenfelter, Yaroslav Bulatov: Training conditional random fields via gradient tree boosting. ICML 2004
- [c47]Pengcheng Wu, Thomas G. Dietterich: Improving SVM accuracy by training on auxiliary data sources. ICML 2004
- 2003
- [c46]Giorgio Valentini, Thomas G. Dietterich: Low Bias Bagged Support Vector Machines. ICML 2003: 752-759
- [c45]
- 2002
- [c44]Dídac Busquets, Ramon López de Mántaras, Carles Sierra, Thomas G. Dietterich: A Multi-agent Architecture Integrating Learning and Fuzzy Techniques for Landmark-Based Robot Navigation. CCIA 2002: 269-281
- [c43]Valentina Bayer Zubek, Thomas G. Dietterich: Pruning Improves Heuristic Search for Cost-Sensitive Learning. ICML 2002: 19-26
- [c42]Thomas G. Dietterich, Dídac Busquets, Ramon López de Mántaras, Carles Sierra: Action Refinement in Reinforcement Learning by Probability Smoothing. ICML 2002: 107-114
- [c41]Giorgio Valentini, Thomas G. Dietterich: Bias-Variance Analysis and Ensembles of SVM. Multiple Classifier Systems 2002: 222-231
- [c40]
- 2001
- [c39]
- [c38]
- [c37]
- [c36]
- [e3]Todd K. Leen, Thomas G. Dietterich, Volker Tresp (Eds.): Advances in Neural Information Processing Systems 13, Papers from Neural Information Processing Systems (NIPS) 2000, Denver, CO, USA. MIT Press 2001
- [e2]Thomas G. Dietterich, Suzanna Becker, Zoubin Ghahramani (Eds.): Advances in Neural Information Processing Systems 14 [Neural Information Processing Systems: Natural and Synthetic, NIPS 2001, December 3-8, 2001, Vancouver, British Columbia, Canada]. MIT Press 2001
- 2000
- [j33]Thomas G. Dietterich: Hierarchical Reinforcement Learning with the MAXQ Value Function Decomposition. J. Artif. Intell. Res. (JAIR) 13: 227-303 (2000)
- [j32]Thomas G. Dietterich: An Experimental Comparison of Three Methods for Constructing Ensembles of Decision Trees: Bagging, Boosting, and Randomization. Machine Learning 40(2): 139-157 (2000)
- [c35]
- [c34]Eric Chown, Thomas G. Dietterich: A Divide and Conquer Approach to Learning from Prior Knowledge. ICML 2000: 143-150
- [c33]Dragos D. Margineantu, Thomas G. Dietterich: Bootstrap Methods for the Cost-Sensitive Evaluation of Classifiers. ICML 2000: 583-590
- [c32]Tony Fountain, Thomas G. Dietterich, Bill Sudyka: Mining IC test data to optimize VLSI testing. KDD 2000: 18-25
- [c31]
- [c30]Valentina Bayer Zubek, Thomas G. Dietterich: A POMDP Approximation Algorithm That Anticipates the Need to Observe. PRICAI 2000: 521-532
- [c29]
1990 – 1999
- 1999
- [c28]Thomas G. Dietterich: State Abstraction in MAXQ Hierarchical Reinforcement Learning. NIPS 1999: 994-1000
- [i3]Thomas G. Dietterich: Hierarchical Reinforcement Learning with the MAXQ Value Function Decomposition. CoRR cs.LG/9905014 (1999)
- [i2]Thomas G. Dietterich: State Abstraction in MAXQ Hierarchical Reinforcement Learning. CoRR cs.LG/9905015 (1999)
- 1998
- [j31]Thomas G. Dietterich: Approximate Statistical Test For Comparing Supervised Classification Learning Algorithms. Neural Computation 10(7): 1895-1923 (1998)
- [c27]
- 1997
- [j30]Thomas G. Dietterich, Richard H. Lathrop, Tomás Lozano-Pérez: Solving the Multiple Instance Problem with Axis-Parallel Rectangles. Artif. Intell. 89(1-2): 31-71 (1997)
- [j29]
- [j28]Thomas G. Dietterich, Nicholas S. Flann: Explanation-Based Learning and Reinforcement Learning: A Unified View. Machine Learning 28(2-3): 169-210 (1997)
- [c26]
- [c25]Prasad Tadepalli, Thomas G. Dietterich: Hierarchical Explanation-Based Reinforcement Learning. ICML 1997: 358-366
- 1996
- [j27]
- [j26]
- [c24]Thomas G. Dietterich, Michael J. Kearns, Yishay Mansour: Applying the Waek Learning Framework to Understand and Improve C4.5. ICML 1996: 96-104
- 1995
- [j25]Thomas G. Dietterich: Overfitting and Undercomputing in Machine Learning. ACM Comput. Surv. 27(3): 326-327 (1995)
- [j24]Thomas G. Dietterich, Ghulum Bakiri: Solving Multiclass Learning Problems via Error-Correcting Output Codes. J. Artif. Intell. Res. (JAIR) 2: 263-286 (1995)
- [j23]Thomas G. Dietterich, Hermann Hild, Ghulum Bakiri: A Comparison of ID3 and Backpropagation for English Text-to-Speech Mapping. Machine Learning 18(1): 51-80 (1995)
- [j22]Dietrich Wettschereck, Thomas G. Dietterich: An Experimental Comparison of the Nearest-Neighbor and Nearest-Hyperrectangle Algorithms. Machine Learning 19(1): 5-27 (1995)
- [c23]Thomas G. Dietterich, Nicholas S. Flann: Explanation-Based Learning and Reinforcement Learning: A Unified View. ICML 1995: 176-184
- [c22]Eun Bae Kong, Thomas G. Dietterich: Error-Correcting Output Coding Corrects Bias and Variance. ICML 1995: 313-321
- [c21]Wei Zhang, Thomas G. Dietterich: A Reinforcement Learning Approach to job-shop Scheduling. IJCAI 1995: 1114-1120
- [c20]
- [i1]Thomas G. Dietterich, Ghulum Bakiri: Solving Multiclass Learning Problems via Error-Correcting Output Codes. CoRR cs.AI/9501101 (1995)
- 1994
- [j21]Hussein Almuallim, Thomas G. Dietterich: Learning Boolean Concepts in the Presence of Many Irrelevant Features. Artif. Intell. 69(1-2): 279-305 (1994)
- [j20]Ajay N. Jain, Thomas G. Dietterich, Richard H. Lathrop, David Chapman, Roger E. Critchlow Jr., Barr E. Bauer, Teresa A. Webster, Tomás Lozano-Pérez: Compass: A shape-based machine learning tool for drug design. Journal of Computer-Aided Molecular Design 8(6): 635-652 (1994)
- [j19]
- 1993
- [j18]
- [c19]Dietrich Wettschereck, Thomas G. Dietterich: Locally Adaptive Nearest Neighbor Algorithms. NIPS 1993: 184-191
- [c18]Thomas G. Dietterich, Ajay N. Jain, Richard H. Lathrop, Tomás Lozano-Pérez: A Comparison of Dynamic Reposing and Tangent Distance for Drug Activity Prediction. NIPS 1993: 216-223
- [c17]Thomas G. Dietterich, Dietrich Wettschereck, Christopher G. Atkeson, Andrew W. Moore: Memory-Based Methods for Regression and Classification. NIPS 1993: 1165-1166
- 1992
- [j17]
- [c16]
- 1991
- [j16]Ashok K. Goel, Tom Bylander, B. Chandrasekaran, Thomas G. Dietterich, Richard M. Keller, Chris Tong: Knowledge Compilation: A Symposium. IEEE Expert 6(2): 71-93 (1991)
- [c15]
- [c14]Thomas G. Dietterich, Ghulum Bakiri: Error-Correcting Output Codes: A General Method for Improving Multiclass Inductive Learning Programs. AAAI 1991: 572-577
- [c13]Giuseppe Cerbone, Thomas G. Dietterich: Knowledge Compilation to Speed Up Numerical Optimisation. AI*IA 1991: 208-217
- [c12]Steve A. Chien, Bradley L. Whitehall, Thomas G. Dietterich, Richard J. Doyle, Brian Falkenhainer, James Garrett, Stephen C. Y. Lu: Machine Learning in Engineering Automation. ML 1991: 577-580
- [c11]Giuseppe Cerbone, Thomas G. Dietterich: Knowledge Compilation to Speed Up Numerical Optimization. ML 1991: 600-604
- [c10]Dietrich Wettschereck, Thomas G. Dietterich: Improving the Performance of Radial Basis Function Networks by Learning Center Locations. NIPS 1991: 1133-1140
- 1990
- [j15]
- [c9]Thomas G. Dietterich, Hermann Hild, Ghulum Bakiri: A Comparative Study of ID3 and Backpropagation for English Text-to-Speech Mapping. ML 1990: 24-31
- [e1]Howard E. Shrobe, Thomas G. Dietterich, William R. Swartout (Eds.): Proceedings of the 8th National Conference on Artificial Intelligence. Boston, Massachusetts, July 29 - August 3, 1990, 2 Volumes. AAAI Press / The MIT Press 1990, ISBN 0-262-51057-X
1980 – 1989
- 1989
- [j14]
- [j13]
- [j12]Nicholas S. Flann, Thomas G. Dietterich: A Study of Explanation-Based Methods for Inductive Learning. Machine Learning 4: 187-226 (1989)
- [c8]
- [c7]
- 1988
- [j11]
- [c6]Caroline N. Koff, Nicholas S. Flann, Thomas G. Dietterich: An Efficient ATMS for Equivalence Relations. AAAI 1988: 182-187
- 1987
- [j10]
- [j9]
- [j8]
- [j7]
- [c5]Nicholas S. Flann, Thomas G. Dietterich, Dan R. Corpon: Forward Chaining Logic Programming with the ATMS. AAAI 1987: 24-29
- 1986
- [j6]Thomas G. Dietterich, Nicholas S. Flann, David C. Wilkins: News and Notes. Machine Learning 1(2): 227-242 (1986)
- [j5]
- [j4]Yves Kodratoff, Gheorghe Tecuci, Thomas G. Dietterich: News and Notes. Machine Learning 1(3): 355-358 (1986)
- [j3]
- [c4]Nicholas S. Flann, Thomas G. Dietterich: Selecting Appropriate Representations for Learning from Examples. AAAI 1986: 460-466
- 1985
- [j2]Thomas G. Dietterich, Ryszard S. Michalski: Discovering Patterns in Sequences of Events. Artif. Intell. 25(2): 187-232 (1985)
- 1984
- [c3]
- 1981
- [j1]Thomas G. Dietterich, Ryszard S. Michalski: Inductive Learning of Structural Descriptions: Evaluation Criteria and Comparative Review of Selected Methods. Artif. Intell. 16(3): 257-294 (1981)
- 1980
- [c2]Thomas G. Dietterich: Applying General Induction Methods to the Card Game Eleusis. AAAI 1980: 218-220
1970 – 1979
- 1979
- [c1]Thomas G. Dietterich, Ryszard S. Michalski: Learning and Generalization of Characteristic Descriptions: Evaluation Criteria and Comparative Review of Selected Methods. IJCAI 1979: 223-231
Coauthor Index
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last updated on 2013-10-02 10:59 CEST by the dblp team