Thomas G. Dietterich

Orcid: 0000-0002-8223-8586

Affiliations:
  • Oregon State University, School of Electrical Engineering and Computer Science


According to our database1, Thomas G. Dietterich authored at least 194 papers between 1979 and 2023.

Collaborative distances:

Awards

ACM Fellow

ACM Fellow 2002, "For contributions to machine learning.".

Timeline

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Bibliography

2023
Hidden Heterogeneity: When to Choose Similarity-Based Calibration.
Trans. Mach. Learn. Res., 2023

Reinforcement Learning with Exogenous States and Rewards.
CoRR, 2023

2022
The familiarity hypothesis: Explaining the behavior of deep open set methods.
Pattern Recognit., 2022

PAC Guarantees and Effective Algorithms for Detecting Novel Categories.
J. Mach. Learn. Res., 2022

Will My Robot Achieve My Goals? Predicting the Probability that an MDP Policy Reaches a User-Specified Behavior Target.
CoRR, 2022

Oracle Analysis of Representations for Deep Open Set Detection.
CoRR, 2022

Conformal Prediction Intervals for Markov Decision Process Trajectories.
CoRR, 2022

ANDEA: Anomaly and Novelty Detection, Explanation, and Accommodation.
Proceedings of the KDD '22: The 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, Washington, DC, USA, August 14, 2022

2021
A Unifying Review of Deep and Shallow Anomaly Detection.
Proc. IEEE, 2021

Deep Convolution for Irregularly Sampled Temporal Point Clouds.
CoRR, 2021

Anomaly and Novelty Detection, Explanation, and Accommodation (ANDEA).
Proceedings of the KDD '21: The 27th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2021

Confidence Calibration for Domain Generalization under Covariate Shift.
Proceedings of the 2021 IEEE/CVF International Conference on Computer Vision, 2021

K-N-MOMDPs: Towards Interpretable Solutions for Adaptive Management.
Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

2020
Discovering Anomalies by Incorporating Feedback from an Expert.
ACM Trans. Knowl. Discov. Data, 2020

DARPA's Role in Machine Learning.
AI Mag., 2020

Conditional mixture models for precipitation data quality control.
Proceedings of the 3rd ACM SIGCAS Conference on Computing and Sustainable Societies, 2020

Solving K-MDPs.
Proceedings of the Thirtieth International Conference on Automated Planning and Scheduling, 2020

2019
Sequential Feature Explanations for Anomaly Detection.
ACM Trans. Knowl. Discov. Data, 2019

Robust artificial intelligence and robust human organizations.
Frontiers Comput. Sci., 2019

Computational sustainability: computing for a better world and a sustainable future.
Commun. ACM, 2019

Three-quarter Sibling Regression for Denoising Observational Data.
Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence, 2019

Deep Anomaly Detection with Outlier Exposure.
Proceedings of the 7th International Conference on Learning Representations, 2019

Benchmarking Neural Network Robustness to Common Corruptions and Perturbations.
Proceedings of the 7th International Conference on Learning Representations, 2019

Anomaly detection in the presence of missing values for weather data quality control.
Proceedings of the Conference on Computing & Sustainable Societies, 2019

2018
Anomaly Detection in the Presence of Missing Values.
CoRR, 2018

Feedback-Guided Anomaly Discovery via Online Optimization.
Proceedings of the 24th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, 2018

Open Category Detection with PAC Guarantees.
Proceedings of the 35th International Conference on Machine Learning, 2018

Discovering and Removing Exogenous State Variables and Rewards for Reinforcement Learning.
Proceedings of the 35th International Conference on Machine Learning, 2018

Efficient Exploration for Constrained MDPs.
Proceedings of the 2018 AAAI Spring Symposia, 2018

Can We Achieve Open Category Detection with Guarantees?
Proceedings of the Workshops of the The Thirty-Second AAAI Conference on Artificial Intelligence, 2018

2017
Interactive visualization for testing Markov Decision Processes: MDPVIS.
J. Vis. Lang. Comput., 2017

Sample-Based Tree Search with Fixed and Adaptive State Abstractions.
J. Artif. Intell. Res., 2017

Incorporating Feedback into Tree-based Anomaly Detection.
CoRR, 2017

Fast Optimization of Wildfire Suppression Policies with SMAC.
CoRR, 2017

Factoring Exogenous State for Model-Free Monte Carlo.
CoRR, 2017

Steps Toward Robust Artificial Intelligence.
AI Mag., 2017

Three New Algorithms to Solve N-POMDPs.
Proceedings of the Thirty-First AAAI Conference on Artificial Intelligence, 2017

2016
Finite Sample Complexity of Rare Pattern Anomaly Detection.
Proceedings of the Thirty-Second Conference on Uncertainty in Artificial Intelligence, 2016

Transductive Optimization of Top k Precision.
Proceedings of the Twenty-Fifth International Joint Conference on Artificial Intelligence, 2016

Incorporating Expert Feedback into Active Anomaly Discovery.
Proceedings of the IEEE 16th International Conference on Data Mining, 2016

2015
PAC optimal MDP planning with application to invasive species management.
J. Mach. Learn. Res., 2015

Systematic Construction of Anomaly Detection Benchmarks from Real Data.
CoRR, 2015

Rise of concerns about AI: reflections and directions.
Commun. ACM, 2015

Who speaks for AI?
AI Matters, 2015

Letter to the Editor: Research Priorities for Robust and Beneficial Artificial Intelligence: An Open Letter.
AI Mag., 2015

Facilitating testing and debugging of Markov Decision Processes with interactive visualization.
Proceedings of the 2015 IEEE Symposium on Visual Languages and Human-Centric Computing, 2015

Improving Automated Email Tagging with Implicit Feedback.
Proceedings of the 28th Annual ACM Symposium on User Interface Software & Technology, 2015

Progressive Abstraction Refinement for Sparse Sampling.
Proceedings of the Thirty-First Conference on Uncertainty in Artificial Intelligence, 2015

α-min: A Compact Approximate Solver For Finite-Horizon POMDPs.
Proceedings of the Twenty-Fourth International Joint Conference on Artificial Intelligence, 2015

ℋC-search for structured prediction in computer vision.
Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2015

MDPVIS: An Interactive Visualization for Testing Markov Decision Processes.
Proceedings of the 2015 AAAI Fall Symposia, Arlington, Virginia, USA, November 12-14, 2015, 2015

Learning Greedy Policies for the Easy-First Framework.
Proceedings of the Twenty-Ninth AAAI Conference on Artificial Intelligence, 2015

2014
Active lmitation learning: formal and practical reductions to I.I.D. learning.
J. Mach. Learn. Res., 2014

Reconstructing Velocities of Migrating Birds from Weather Radar - A Case Study in Computational Sustainability.
AI Mag., 2014

Gaussian Approximation of Collective Graphical Models.
Proceedings of the 31th International Conference on Machine Learning, 2014

Learnability of the Superset Label Learning Problem.
Proceedings of the 31th International Conference on Machine Learning, 2014

Prune-and-Score: Learning for Greedy Coreference Resolution.
Proceedings of the 2014 Conference on Empirical Methods in Natural Language Processing, 2014

Learning Scripts as Hidden Markov Models.
Proceedings of the Twenty-Eighth AAAI Conference on Artificial Intelligence, 2014

State Aggregation in Monte Carlo Tree Search.
Proceedings of the Twenty-Eighth AAAI Conference on Artificial Intelligence, 2014

2013

Approximate Inference in Collective Graphical Models.
Proceedings of the 30th International Conference on Machine Learning, 2013

Learning to Detect Basal Tubules of Nematocysts in SEM Images.
Proceedings of the 2013 IEEE International Conference on Computer Vision Workshops, 2013

Zero-Shot Learning and Detection of Teeth in Images of Bat Skulls.
Proceedings of the 2013 IEEE International Conference on Computer Vision Workshops, 2013

Guiding Scientific Discovery with Explanations Using DEMUD.
Proceedings of the Twenty-Seventh AAAI Conference on Artificial Intelligence, 2013

Approximate Bayesian Inference for Reconstructing Velocities of Migrating Birds from Weather Radar.
Proceedings of the Twenty-Seventh AAAI Conference on Artificial Intelligence, 2013

PAC Optimal Planning for Invasive Species Management: Improved Exploration for Reinforcement Learning from Simulator-Defined MDPs.
Proceedings of the Twenty-Seventh AAAI Conference on Artificial Intelligence, 2013

2012
An Ensemble Architecture for Learning Complex Problem-Solving Techniques from Demonstration.
ACM Trans. Intell. Syst. Technol., 2012

Active Imitation Learning via Reduction to I.I.D. Active Learning.
Proceedings of the Twenty-Eighth Conference on Uncertainty in Artificial Intelligence, 2012

Inferring Strategies from Limited Reconnaissance in Real-time Strategy Games.
Proceedings of the Twenty-Eighth Conference on Uncertainty in Artificial Intelligence, 2012

A Conditional Multinomial Mixture Model for Superset Label Learning.
Proceedings of the Advances in Neural Information Processing Systems 25: 26th Annual Conference on Neural Information Processing Systems 2012. Proceedings of a meeting held December 3-6, 2012

Machine learning for computational sustainability.
Proceedings of the 2012 International Green Computing Conference, 2012

2011
Spatiotemporal Models for Data-Anomaly Detection in Dynamic Environmental Monitoring Campaigns.
ACM Trans. Sens. Networks, 2011

FolderPredictor: Reducing the cost of reaching the right folder.
ACM Trans. Intell. Syst. Technol., 2011

Learning Rules from Incomplete Examples via Implicit Mention Models.
Proceedings of the 3rd Asian Conference on Machine Learning, 2011

Automatic Discovery and Transfer of Task Hierarchies in Reinforcement Learning.
AI Mag., 2011

Stacked spatial-pyramid kernel: An object-class recognition method to combine scores from random trees.
Proceedings of the IEEE Workshop on Applications of Computer Vision (WACV 2011), 2011

Inverting Grice's Maxims to Learn Rules from Natural Language Extractions.
Proceedings of the Advances in Neural Information Processing Systems 24: 25th Annual Conference on Neural Information Processing Systems 2011. Proceedings of a meeting held 12-14 December 2011, 2011

Collective Graphical Models.
Proceedings of the Advances in Neural Information Processing Systems 24: 25th Annual Conference on Neural Information Processing Systems 2011. Proceedings of a meeting held 12-14 December 2011, 2011

Learning Probabilistic Behavior Models in Real-Time Strategy Games.
Proceedings of the Seventh AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment, 2011

Incorporating Boosted Regression Trees into Ecological Latent Variable Models.
Proceedings of the Twenty-Fifth AAAI Conference on Artificial Intelligence, 2011

2010
Machine Learning Methods for High Level Cyber Situation Awareness.
Proceedings of the Cyber Situational Awareness - Issues and Research, 2010

Cyber SA: Situational Awareness for Cyber Defense.
Proceedings of the Cyber Situational Awareness - Issues and Research, 2010

Haar Random Forest Features and SVM Spatial Matching Kernel for Stonefly Species Identification.
Proceedings of the 20th International Conference on Pattern Recognition, 2010

The life and times of files and information: a study of desktop provenance.
Proceedings of the 28th International Conference on Human Factors in Computing Systems, 2010

Reinforcement Learning Via Practice and Critique Advice.
Proceedings of the Twenty-Fourth AAAI Conference on Artificial Intelligence, 2010

2009
A family of large margin linear classifiers and its application in dynamic environments.
Stat. Anal. Data Min., 2009

Interacting meaningfully with machine learning systems: Three experiments.
Int. J. Hum. Comput. Stud., 2009

Detecting and correcting user activity switches: algorithms and interfaces.
Proceedings of the 14th International Conference on Intelligent User Interfaces, 2009

Discovering frequent work procedures from resource connections.
Proceedings of the 14th International Conference on Intelligent User Interfaces, 2009

Machine Learning in Ecosystem Informatics and Sustainability.
Proceedings of the IJCAI 2009, 2009

Learning non-redundant codebooks for classifying complex objects.
Proceedings of the 26th Annual International Conference on Machine Learning, 2009


Dictionary-free categorization of very similar objects via stacked evidence trees.
Proceedings of the 2009 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR 2009), 2009

Machine Learning and Ecosystem Informatics: Challenges and Opportunities.
Proceedings of the Advances in Machine Learning, 2009

2008
Automated insect identification through concatenated histograms of local appearance features: feature vector generation and region detection for deformable objects.
Mach. Vis. Appl., 2008

Structured machine learning: the next ten years.
Mach. Learn., 2008

Learning first-order probabilistic models with combining rules.
Ann. Math. Artif. Intell., 2008

Learning MDP Action Models Via Discrete Mixture Trees.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2008

Learning visual dictionaries and decision lists for object recognition.
Proceedings of the 19th International Conference on Pattern Recognition (ICPR 2008), 2008

Automatic discovery and transfer of MAXQ hierarchies.
Proceedings of the Machine Learning, 2008

Integrating Multiple Learning Components through Markov Logic.
Proceedings of the Twenty-Third AAAI Conference on Artificial Intelligence, 2008

2007
AAAI-07 Workshop Reports.
AI Mag., 2007

Automated Insect Identification through Concatenated Histograms of Local Appearance Features.
Proceedings of the 8th IEEE Workshop on Applications of Computer Vision (WACV 2007), 2007

Probabilistic Models for Anomaly Detection in Remote Sensor Data Streams.
Proceedings of the UAI 2007, 2007

Toward harnessing user feedback for machine learning.
Proceedings of the 12th International Conference on Intelligent User Interfaces, 2007

Active EM to reduce noise in activity recognition.
Proceedings of the 12th International Conference on Intelligent User Interfaces, 2007

Real-Time Detection of Task Switches of Desktop Users.
Proceedings of the IJCAI 2007, 2007

Improving Intelligent Assistants for Desktop Activities.
Proceedings of the Interaction Challenges for Intelligent Assistants, 2007

Machine Learning in Ecosystem Informatics.
Proceedings of the Discovery Science, 10th International Conference, 2007

07161 Abstracts Collection -- Probabilistic, Logical and Relational Learning - A Further Synthesis.
Proceedings of the Probabilistic, Logical and Relational Learning - A Further Synthesis, 15.04., 2007

Principal Curvature-Based Region Detector for Object Recognition.
Proceedings of the 2007 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR 2007), 2007

2006
A hybrid learning system for recognizing user tasks from desktop activities and email messages.
Proceedings of the 11th International Conference on Intelligent User Interfaces, 2006

Fewer clicks and less frustration: reducing the cost of reaching the right folder.
Proceedings of the 11th International Conference on Intelligent User Interfaces, 2006

A Hierarchical Object Recognition System Based on Multi-scale Principal Curvature Regions.
Proceedings of the 18th International Conference on Pattern Recognition (ICPR 2006), 2006

Reinforcement Matching Using Region Context.
Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2006

2005
Integrating Learning from Examples into the Search for Diagnostic Policies.
J. Artif. Intell. Res., 2005

Learning from Sparse Data by Exploiting Monotonicity Constraints.
Proceedings of the UAI '05, 2005

TaskTracer: a desktop environment to support multi-tasking knowledge workers.
Proceedings of the 10th International Conference on Intelligent User Interfaces, 2005

Learning first-order probabilistic models with combining rules.
Proceedings of the Machine Learning, 2005

05051 Abstracts Collection - Probabilistic, Logical and Relational Learning - Towards a Synthesis.
Proceedings of the Probabilistic, Logical and Relational Learning - Towards a Synthesis, 30. January, 2005

05051 Executive Summary - Probabilistic, Logical and Relational Learning - Towards a Synthesis.
Proceedings of the Probabilistic, Logical and Relational Learning - Towards a Synthesis, 30. January, 2005


2004
Bias-Variance Analysis of Support Vector Machines for the Development of SVM-Based Ensemble Methods.
J. Mach. Learn. Res., 2004

Improving SVM accuracy by training on auxiliary data sources.
Proceedings of the Machine Learning, 2004

Training conditional random fields via gradient tree boosting.
Proceedings of the Machine Learning, 2004

2003
Model-based Policy Gradient Reinforcement Learning.
Proceedings of the Machine Learning, 2003

Low Bias Bagged Support Vector Machines.
Proceedings of the Machine Learning, 2003

2002
Machine Learning for Sequential Data: A Review.
Proceedings of the Structural, 2002

Bias-Variance Analysis and Ensembles of SVM.
Proceedings of the Multiple Classifier Systems, Third International Workshop, 2002

Pruning Improves Heuristic Search for Cost-Sensitive Learning.
Proceedings of the Machine Learning, 2002

Action Refinement in Reinforcement Learning by Probability Smoothing.
Proceedings of the Machine Learning, 2002

A Multi-agent Architecture Integrating Learning and Fuzzy Techniques for Landmark-Based Robot Navigation.
Proceedings of the Topics in Artificial Intelligence, 5th Catalonian Conference on AI, 2002

2001
Support Vectors for Reinforcement Learning.
Proceedings of the Principles of Data Mining and Knowledge Discovery, 2001

Stabilizing Value Function Approximation with the BFBP Algorithm.
Proceedings of the Advances in Neural Information Processing Systems 14 [Neural Information Processing Systems: Natural and Synthetic, 2001

Batch Value Function Approximation via Support Vectors.
Proceedings of the Advances in Neural Information Processing Systems 14 [Neural Information Processing Systems: Natural and Synthetic, 2001

2000
An Experimental Comparison of Three Methods for Constructing Ensembles of Decision Trees: Bagging, Boosting, and Randomization.
Mach. Learn., 2000

Hierarchical Reinforcement Learning with the MAXQ Value Function Decomposition.
J. Artif. Intell. Res., 2000

An Overview of MAXQ Hierarchical Reinforcement Learning.
Proceedings of the Abstraction, 2000

A POMDP Approximation Algorithm That Anticipates the Need to Observe.
Proceedings of the PRICAI 2000, Topics in Artificial Intelligence, 6th Pacific Rim International Conference on Artificial Intelligence, Melbourne, Australia, August 28, 2000

Ensemble Methods in Machine Learning.
Proceedings of the Multiple Classifier Systems, First International Workshop, 2000

Mining IC test data to optimize VLSI testing.
Proceedings of the sixth ACM SIGKDD international conference on Knowledge discovery and data mining, 2000

Bootstrap Methods for the Cost-Sensitive Evaluation of Classifiers.
Proceedings of the Seventeenth International Conference on Machine Learning (ICML 2000), Stanford University, Stanford, CA, USA, June 29, 2000

A Divide and Conquer Approach to Learning from Prior Knowledge.
Proceedings of the Seventeenth International Conference on Machine Learning (ICML 2000), Stanford University, Stanford, CA, USA, June 29, 2000

The Divide-and-Conquer Manifesto.
Proceedings of the Algorithmic Learning Theory, 11th International Conference, 2000

1999
State Abstraction in MAXQ Hierarchical Reinforcement Learning.
Proceedings of the Advances in Neural Information Processing Systems 12, [NIPS Conference, Denver, Colorado, USA, November 29, 1999

1998
Approximate Statistical Tests for Comparing Supervised Classification Learning Algorithms.
Neural Comput., 1998

The MAXQ Method for Hierarchical Reinforcement Learning.
Proceedings of the Fifteenth International Conference on Machine Learning (ICML 1998), 1998

1997
Explanation-Based Learning and Reinforcement Learning: A Unified View.
Mach. Learn., 1997

Machine-Learning Research.
AI Mag., 1997

Solving the Multiple Instance Problem with Axis-Parallel Rectangles.
Artif. Intell., 1997

Hierarchical Explanation-Based Reinforcement Learning.
Proceedings of the Fourteenth International Conference on Machine Learning (ICML 1997), 1997

Pruning Adaptive Boosting.
Proceedings of the Fourteenth International Conference on Machine Learning (ICML 1997), 1997

1996
Machine Learning.
ACM Comput. Surv., 1996

Applying the Waek Learning Framework to Understand and Improve C4.5.
Proceedings of the Machine Learning, 1996

1995
An Experimental Comparison of the Nearest-Neighbor and Nearest-Hyperrectangle Algorithms.
Mach. Learn., 1995

A Comparison of ID3 and Backpropagation for English Text-to-Speech Mapping.
Mach. Learn., 1995

Solving Multiclass Learning Problems via Error-Correcting Output Codes.
J. Artif. Intell. Res., 1995

Overfitting and Undercomputing in Machine Learning.
ACM Comput. Surv., 1995

High-Performance Job-Shop Scheduling With A Time-Delay TD-lambda Network.
Proceedings of the Advances in Neural Information Processing Systems 8, 1995

A Reinforcement Learning Approach to job-shop Scheduling.
Proceedings of the Fourteenth International Joint Conference on Artificial Intelligence, 1995

Error-Correcting Output Coding Corrects Bias and Variance.
Proceedings of the Machine Learning, 1995

1994
Editorial: New Editorial Board Members.
Mach. Learn., 1994

Compass: A shape-based machine learning tool for drug design.
J. Comput. Aided Mol. Des., 1994

Learning Boolean Concepts in the Presence of Many Irrelevant Features.
Artif. Intell., 1994

1993
Locally Adaptive Nearest Neighbor Algorithms.
Proceedings of the Advances in Neural Information Processing Systems 6, 1993

A Comparison of Dynamic Reposing and Tangent Distance for Drug Activity Prediction.
Proceedings of the Advances in Neural Information Processing Systems 6, 1993

Memory-Based Methods for Regression and Classification.
Proceedings of the Advances in Neural Information Processing Systems 6, 1993

1992
Editorial.
Mach. Learn., 1992

On Learning More Concepts.
Proceedings of the Ninth International Workshop on Machine Learning (ML 1992), 1992

1991
Knowledge Compilation: A Symposium.
IEEE Expert, 1991

Improving the Performance of Radial Basis Function Networks by Learning Center Locations.
Proceedings of the Advances in Neural Information Processing Systems 4, 1991

Machine Learning in Engineering Automation.
Proceedings of the Eighth International Workshop (ML91), 1991

Knowledge Compilation to Speed Up Numerical Optimization.
Proceedings of the Eighth International Workshop (ML91), 1991

Knowledge Compilation to Speed Up Numerical Optimisation.
Proceedings of the Trends in Artificial Intelligence, 1991

Error-Correcting Output Codes: A General Method for Improving Multiclass Inductive Learning Programs.
Proceedings of the 9th National Conference on Artificial Intelligence, 1991

Learning with Many Irrelevant Features.
Proceedings of the 9th National Conference on Artificial Intelligence, 1991

1990
Exploratory Research in Machine Learning.
Mach. Learn., 1990

A Comparative Study of ID3 and Backpropagation for English Text-to-Speech Mapping.
Proceedings of the Machine Learning, 1990

1989
A Study of Explanation-Based Methods for Inductive Learning.
Mach. Learn., 1989

News and Notes.
Mach. Learn., 1989

What Good Are Experiments?.
Proceedings of the Sixth International Workshop on Machine Learning (ML 1989), 1989

Limitations on Inductive Learning.
Proceedings of the Sixth International Workshop on Machine Learning (ML 1989), 1989

1988
A model of the mechanical design process based on empirical data.
Artif. Intell. Eng. Des. Anal. Manuf., 1988

An Efficient ATMS for Equivalence Relations.
Proceedings of the 7th National Conference on Artificial Intelligence, 1988

1987
Forward Chaining Logic Programming with the ATMS.
Proceedings of the 6th National Conference on Artificial Intelligence. Seattle, 1987

1986
News and Notes.
Mach. Learn., 1986

News and Notes.
Mach. Learn., 1986

Learning at the Knowledge Level.
Mach. Learn., 1986

Selecting Appropriate Representations for Learning from Examples.
Proceedings of the 5th National Conference on Artificial Intelligence. Philadelphia, 1986

1985
Discovering Patterns in Sequences of Events.
Artif. Intell., 1985

1984
Learning About Systems That Contain State Variables.
Proceedings of the National Conference on Artificial Intelligence. Austin, 1984

1981
Inductive Learning of Structural Descriptions: Evaluation Criteria and Comparative Review of Selected Methods.
Artif. Intell., 1981

1980
Applying General Induction Methods to the Card Game Eleusis.
Proceedings of the 1st Annual National Conference on Artificial Intelligence, 1980

1979
Learning and Generalization of Characteristic Descriptions: Evaluation Criteria and Comparative Review of Selected Methods.
Proceedings of the Sixth International Joint Conference on Artificial Intelligence, 1979


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