Links to online publications are given for selected publications below. Publications by graduate students that I supervised, but for which I was not a coauthor, are given under Graduate Student Supervision and Committees on my main index page.


Selected publications organized by (overlapping) areas

Papers in the following sections tend to show a significant concern with synthesis, and include concerns with integrative intelligence.

  • Inductive/Analytic Hybrids

  • Problem Solving as Categorization

  • Adapting Lessons of Supervised Learning for Unupervised Learning

  • Cognitive Modeling

  • Interactive Induction

    Papers in the following sections are more tool-based or engineering-based, but many still show concerns with synthesis and overlap with papers above.

  • Incremental Learning

  • Conceptual Clustering

  • Data Mining

  • Applications (medical, engineering)

  • Rule-based Learning


    Publications organized chronologically by venue type

    Archival Periodicals

    Fisher, D. (1987) "Knowledge Acquisition Via Incremental Conceptual Clustering," Machine Learning, 2, 139--172. Reprinted in J. Shavlik & T. Dietterich (eds.), Readings in Machine Learning, 267--283, Morgan Kaufmann, 1990.

    Gennari, J., Langley, P., & Fisher, D. (1989). "Models of Incremental Concept Formation," Artificial Intelligence, 40, 11--62.

    Fisher, D., & Chan, P. (1990). "Statistical Guidance in Symbolic Learning," Annals of Mathematics and Artificial Intelligence, 2, 135--148.

    Fisher, D., & Langley, P. (1990). "The Structure and Formation of Natural Categories," in G. Bower (ed.), The Psychology of Learning and Motivation, 26, San Diego, CA: Academic Press, 241--284.

    Fisher, D., & Hapanyengwi, G. (1993). "Database Management and Analysis Tools of Machine Learning," Journal of Intelligent Information Systems, 2, 5--38.

    Fisher, D., & Yoo, J. (1993). "Problem solving, categorization, and concept learning: A unifying view," in G. Nakamura, R. Taraban, & D. Medin (eds.), The Psychology of Learning and Motivation, 29, San Diego, CA: Academic Press, 219--255.

    Fisher, D., Xu, L., Carnes, R., Reich, Y., Fenves, S., Chen, J., Shiavi, R., Biswas, G., & Weinberg, J. (1993). "Applying AI clustering to engineering tasks," IEEE Expert, 8, 6, 51--60.

    Evans, B., & Fisher, D. (1994). "Process delay analysis using decision tree induction," IEEE Expert, 9, 1, 60--66.

    Srinivasan, K., & Fisher, D. (1995). "Machine learning approaches to estimating software development effort," IEEE Transactions on Software Engineering, 21, 2, 126--137.
    Reprinted in D. Zhang & J. Tsai, (eds.), Machine Learning Applications in Software Engineering, World Scientific Press, 2005.
    An addendum to `Machine Learning Approaches to Estimating Software Development Effort' (IEEE TSE, 1995)

    Fisher, D. (1996). "Iterative Optimization and Simplification of Hierarchical Clusterings," Journal of Artificial Intelligence Research, 4, 147--179.

    Biswas, G., Weinberg, J., & Fisher, D. (1998). IEEE Transactions on Systems, Man, and Cybernetics, 28, 2, 219--230.

    Frey, L., Li, C., Talbert, D., & Fisher, D. (1998). "A review of the Fourteenth International Conference on Machine Learning," Intelligent Data Analysis, 2, 3, 245--255.

    Fisher, D. (2001). Unsupervised Learning (Editorial), Machine Learning, 45, 1, 5--7. (Special issue editor, 30 submissions, 2 installments).

    Fisher, D. (2002). Unsupervised Learning (Editorial). Machine Learning, 47, 1, 5--6. (Special Issue editor).

    Fisher, D., Edgerton, M., Chen, Z., Tang, L., & Frey, L. (2006). "Backward Chaining Rule Induction," Journal of Intelligent Data Analysis, 10, 5, 397--417.

    Waitman, L. R., Fisher, D., & King, P. H. (2006). "Bootstrapping rule induction to achieve rule stability and reduction," Journal of Intelligent Information Systems, 27, 49--77.

    Whitley, K., Novick, L., & Fisher, D. (2006). "Evidence in favor of visual representation for the dataflow paradigm: An experiment testing LabVIEW's comprehensibility," International Journal of Human-Computer Studies, 64, 4, 281--303.

    Edgerton, M., Fisher, D., Tang, L., Frey, L., & Chen, Z. (2007). "Data mining for gene networks relevant to poor prognosis in lung cancer via backward-chaining rule induction: An implementation in lung cancer research," Cancer Informatics.

    Books and Proceedings (edited)

    Fisher, D., Pazzani, M., & Langley, P. (eds.), (1991). Concept Formation: Experience and Knowledge in Unsupervised Learning. San Mateo, CA: Morgan Kaufmann, 472 pages, 15 chapters.

    Fisher, D., & Lenz, H.-J. (eds.), (1996). Learning from Data: Lecture Notes in Statistics. Springer Verlag, 450 pages, 42 chapters.

    Fisher, D. (ed.), (1997). Proceedings of the Fourteenth International Conference on Machine Learning Morgan Kaufmann, 430 pages, 49 papers.

    Hoffman, F., Hand, D., Adams, N., Fisher, D., & Guimaraes, G. (eds.), (2001). Advances in Intelligent Data Analysis. Proceedings of the 4th International Conference in Intelligent Data Analysis, Springer, 384 pages, 38 papers.

    Chapters in Self-Edited Books

    Fisher, D., & Pazzani, M. (1991). "Computational Models of Concept Induction," in Fisher, D., Pazzani, M., & Langley, P. (eds.), Concept Formation: Experience and Knowledge in Unsupervised Learning. San Mateo, CA: Morgan Kaufmann, 3--44.

    Fisher, D., & Pazzani, M. (1991). "Theory-Guided Concept Formation," in Fisher, D., Pazzani, M., & Langley, P. (eds.), Concept Formation: Experience and Knowledge in Unsupervised Learning. San Mateo, CA: Morgan Kaufmann, 165--178.

    Fisher, D., & Pazzani, M. (1991). "Concept Formation in Context," in Fisher, D., Pazzani, M., & Langley, P. (eds.), Concept Formation: Experience and Knowledge in Unsupervised Learning. San Mateo, CA: Morgan Kaufmann, 307--322.

    Yoo, J., & Fisher, D. (1991). "Concept Formation over Problem-Solving Experience," in Fisher, D., Pazzani, M., & Langley, P. (eds.), Concept Formation: Experience and Knowledge in Unsupervised Learning. San Mateo, CA: Morgan Kaufmann, 279--306. (see Inductive/Analytic Hybrids).

    Other Book Chapters

    Fisher, D., & Langley, P. (1986). "Methods of conceptual clustering and their relation to numerical taxonomy," in W. Gale (ed.), Artificial Intelligence and Statistics. Addison-Wesley, 77--116.

    Biswas, G., Goldman, S., Fisher, D., Bhuva, B., & Glewwe, (1995). "Assessing Design Activity in Complex CMOS Circuit Design," in P. Nichols, S. Chipman, & B. Brennan (eds.), Cognitively Diagnostic Assessment, Lawrence Erlbaum, 167--188.

    Fisher, D. (2002). "Conceptual Clustering," in W. Klosgen and J. Zytkow (eds.), Handbook of Data Mining and Knowledge Discovery, Oxford University Press, 388--396, Chapter 16.5.2. preprint

    Evans, R., & Fisher, D. (2002). "Using decision tree induction to minimize process delays in the printing industry," in W. Klosgen and J. Zytkow (Eds.), Handbook of Data Mining and Knowledge Discovery. Oxford University Press, 874--881. preprint

    AAAI and IJCAI Conferences

    Fisher, D., & Langley, P. (1985). "Approaches to Conceptual Clustering," Proceedings of the International Joint Conference on Artificial Intelligence, Los Angeles, CA: Morgan Kaufmann, 691--697.

    Schlimmer, J., & Fisher, D. (1986). "A Case Study of Incremental Concept Formation," Proceedings of the Fifth National Conference on Artificial Intelligence, Philadelphia, PA: Morgan Kaufmann, 496--501.

    Fisher, D. (1987). "Improving Inference Through Conceptual Clustering," Proceedings of the Sixth National Conference on Artificial Intelligence, Seattle, WA: Morgan Kaufmann, 461--465.

    Fisher, D. (1988). "A Computational Account of Basic Level and Typicality Effects", Proceedings of the Seventh National Conference on Artificial Intelligence. Minneapolis, MN: Morgan Kaufmann, 233--238.

    Fisher, D. (1989). "Noise-Tolerant Conceptual Clustering" Proceedings of the International Joint Conference on Artificial Intelligence, Detroit, MI: Morgan Kaufmann, 825--830.

    Fisher, D., & McKusick, K. (1989). "An Empirical Comparison of ID3 and Back-propagation" Proceedings of the International Joint Conference on Artificial Intelligence, Detroit, MI: Morgan Kaufmann, 788--793.

    Yoo, J., & Fisher, D. (1991). "Concept formation over explanations and problem-solving experiences" Proceedings of the International Joint Conference on Artificial Intelligence, Sydney, Australia: Morgan Kaufmann, 630--636.

    Ortega, J., & Fisher, D. (1995). "Flexibly exploiting prior knowledge in empirical learning," Proceedings of the International Joint Conference on Artificial Intelligence, (pp. 1041--1047). Montreal, Canada: AAAI Press.

    International Conferences and Workshops on Machine Learning

    Fisher, D. (1985). "A Proposed Method of Conceptual Clustering for Structured and Decomposable Objects," in the Proceedings of the Third International Machine Learning Workshop, Skytop, PA, 38--40.

    Fisher, D. (1987). "Conceptual Clustering, Learning from Examples, and Inference," Proceedings of the Fourth International Workshop on Machine Learning. Irvine, CA: Morgan Kaufmann.

    Fisher, D., & Schlimmer, J. (1988). "Concept Simplification and Prediction Accuracy," Proceedings of the Fifth International Machine Learning Conference. Ann Arbor, MI: Morgan Kaufmann.

    Fisher, D., McKusick, K., Mooney, R., Shavlik, J., & Towell, G. (1989). "Processing Issues in Comparisons of Symbolic and Connectionist Learning Systems" Sixth International Machine Learning Workshop, Ithaca, NY: Morgan Kaufmann.

    Yang, H., & Fisher, D. (1989). "Conceptual Clustering of Means-Ends Plans," Sixth International Machine Learning Workshop, Ithaca, NY: Morgan Kaufmann.

    Yoo, J., & Fisher, D. (1989). "Conceptual Clustering of Explanations," Sixth International Machine Learning Workshop, Ithaca, NY: Morgan Kaufmann.

    Carlson, B., Weinberg, J., & Fisher, D. (1990). "Managing Search Using Incremental Conceptual Clustering" Seventh International Conference on Machine Learning. Austin, TX: Morgan Kaufmann.

    Fisher, D., & Yoo, J. (1991). "Combining evidence from deep and surface features" Proceedings of the International Workshop on Machine Learning, Chicago, IL: Morgan Kaufmann.

    Yoo, J., & Fisher, D. (1991). "Identifying cost-effective boundaries of operationality" Proceedings of the International Workshop on Machine Learning, Chicago, IL: Morgan Kaufmann.

    Fisher, D., Xu, L., & Zard, N. (1992). "Ordering Effects in Clustering," Proceedings of the Eighth International Machine Learning Conference, Aberdeen, UK: Morgan Kaufmann.

    Talbert, D., & Fisher, D. (1999). "OPT-KD: An Algorithm for Optimizing KD-Trees" Proceedings of the Sixteenth International Conference on Machine Learning, Bled, Slovenia (398--405). San Francisco, CA: Morgan Kaufmann.

    Conferences of the Cognitive Science Society

    Silber, J., & Fisher, D. (1989). "A Model of Natural Category Structure and its Behavioral Implications," Proceedings of the Eleventh Annual Conference of the Cognitive Science Society, Ann Arbor, MI: Lawrence Erlbaum, 884--891.

    Billman, D., Fisher, D., Gluck, M., Langley, P., & Pazzani, M. (1990). "Computational Models of Category Learning" (symposia), Proceedings of the Twelfth Annual Conference of the Cognitive Science Society, Boston, MA: Lawrence Erlbaum, 989--996.

    Whitley, K., Novick, L., & Fisher, D. (2001). "Advantages of a visual representation for computer programming" (abstract), Proceedings of the Twenty-Third Annual Meeting of the Cognitive Science Society, Edinburgh, Scotland.

    Frey, L., & Fisher, D. (2003). "Augmented Naive Bayesian Model of Classification Learning," Proceedings of the Twenty-Fifth Annual Conference of the Cognitive Science Society Boston, MA (on CD).

    Data Mining and Data Analysis Conferences and Workshops

    Fisher, D. (1995). "Optimization and Simplification of Hierarchical Clusterings," First International Conference on Knowledge Discovery in Databases, Montreal, Canada: AAAI Press, 118--123.

    Frey, L., & Fisher, D. (1999). "Modeling Decision Tree Performance with the Power Law" Proceedings of the Seventh International Workshop on Artificial Intelligence and Statistics, Ft. Lauderdale, FL: Morgan Kaufmann, 59--65.

    Talbert, D., & Fisher, D. (1999). "Exploiting Sample-Data Distributions to Reduce the Cost of Nearest-Neighbor Searches with KD-Trees," Advances in Intelligent Data Analysis, Lecture Notes on Computer Science No. 1642 (Third International Symposium on Intelligent Data Analysis), Amsterdam, Netherlands: Springer, 407--414.

    Talbert, D. & Fisher, D. (2000). "An Empirical Analysis of Techniques for Constructing and Searching K-Dimensional Trees," Proceedings of the Sixth International Conference on Knowledge Discovery and Data Mining, AAAI Press, 26--33.

    Frey, L., Fisher, D., Tsamardinos, I., Aliferis, C., & Statnikov, A. (2003). "Identifying Markov Blankets with Decision Tree Induction," Third IEEE International Conference on Data Mining, Melbourne, FL, 59-66.

    Waitman, L. R., Fisher, D., & King, P. H. (2003). "Bootstrapping rule induction," Third IEEE International Conference on Data Mining, Melbourne, FL, 677-680.

    Fisher, D., Edgerton, M., Tang, L., Frey, L., & Chen, Z. (2005). "Searching for Meaningful Feature Interactions with Backward-Chaining Rule Induction," Advances in Intelligent Data Analysis VI, Lecture Notes on Computer Science No. 3646 (Sixth Biennial Conference on Intelligent Data Analysis), Madrid, Spain: Springer, 86--96.

    Other Conferences, Workshops, and Symposia

    Ortega, J., Lee, G., & Fisher, D. (1989). "Representation Issues in Learning from Examples" Second International Conference on Industrial and Engineering Applications of Artificial Intelligence and Expert Systems, Tullahoma, TN: ACM Press.

    Rodriguez-Moscoso, J., & Fisher, D. (1989). "A Connectionist Model of Intelligent, Real-Time Traffic Control" Second International Workshop on Neural Networks and Their Applications (Neuro-Nimes).

    Rodriguez-Moscoso, J., & Fisher, D. (1989). "Intelligent, Real-Time Traffic Control: A Connectionist Model" Second International Conference on Industrial and Engineering Applications of Artificial Intelligence and Expert Systems, Tullahoma, TN: ACM Press.

    Fisher D., Yang, H., & Yoo, J. (1990). "Case-Based and Abstraction-Based Reasoning" AAAI Symposium on Case-Based Reasoning, Palo Alto, CA: AAAI Press.

    Yang, H., Franke, H., & Fisher D. (1990). "Planning, Replanning, and Learning with an Abstraction Hierarchy" AAAI Symposium on Planning in Uncertain Environments, Palo Alto, CA: AAAI Press.

    Yang, H., Fisher D., & Franke, H. (1990). "Improving Planning Efficiency by Conceptual Clustering" Third International Conference on Industrial and Engineering Applications of Artificial Intelligence and Expert Systems, ACM Press.

    Fisher, D., Subramanian, D., & Tadepalli, P. (1992). "An overview of current research on knowledge compilation and speedup learning." Workshop on Knowledge Compilation and Speedup Learning, Aberdeen, UK.

    Fisher, D., Manganaris, S., & Yoo, J. (1992). "Clustering Approaches to Speedup Learning," Workshop on Knowledge Compilation and Speedup Learning, Aberdeen, UK.

    Fisher, D., Carnes, R., Yang, H., & Yoo, J. (1992). "Basic Levels of Problem Solving and Related Phenomena," AAAI Workshop on Approximations and Abstractions, San Jose, CA.

    Carnes, R., & Fisher, D. (1992). "Inductive Learning Approaches to Sensor Placement and Diagnosis," Second International Workshop on Principles of Diagnosis, Rosario, WA.

    Fisher, D. (1993). "Ordering Effects in Incremental Learning," AAAI Spring Symposium on Training Issues in Incremental Learning, Palo Alto, CA.

    Fisher, D., Ortega, J., & Gallaher, M. (1993). "Induction over All: A Hybrid Approach to Speedup Learning," Third International Workshop on Knowledge Compilation and Speedup Learning, Amherst, MA.

    Manganaris, S., Fisher, D., & Kulkarni, D. (1993). "Towards a Machine Learning Framework for Acquiring and Exploiting Monitoring and Diagnostic Knowledge," The Eleventh International Conference on Applications of AI, Orlando, FL: International Society for Optical Engineering.

    Manganaris, S., Fisher, D., & Kulkarni, D. (1993). "Induction of Operating Modes for Monitoring," The Seventh Annual Space Operations, Applications, and Research Symposium, Houston, TX.

    Ortega, J., & Fisher, D. (1993). "Inductive Speedup Learning Revisited with FOIL," Third International Workshop on Knowledge Compilation and Speedup Learning, Amherst, MA.

    Yang, H., & Fisher, D. (1993). "Planning Speedup by Learning, Reusing, and Patching Macro Operators," Third International Workshop on Knowledge Compilation and Speedup Learning, Amherst, MA.

    Manganaris, S., & Fisher, D. (1994). "Learning Time Series for Intelligent Monitoring," Third International Symposium on Artificial Intellegence, Robotics, and Automation for Space (i-SAIRAS), pp. 71--74, Pasadena, CA.

    Fisher, D., & Talbert, D. (1997). "Inference using Probablistic Concept Trees," Sixth International Workshop on Artificial Intelligence and Statistics, Ft. Lauderdale, FL.

    Balac, N., Gaines, D. & Fisher, D. (2000). Using Regression Trees to Learn Action Models. Proceedings of the IEEE Systems, Man, and Cybernetics Conference, Nashville.

    Balac, N., Gaines, D., & Fisher, D. (2000). Learning Action Models for Navigation in Noisy Environments. International Conference on Machine Learning of Spatial Knowledge, Palo Alto.

    Balac, N., Gaines, D., Fisher, D., & Thongchai, S. (2001). Learning Action Models to Support Efficient Navigation Planning for Unmanned Ground Vehicles. In Proceedings of SPIE Unmanned Ground Vehicle Technology Conference, Orlando.

    Frey, L. J., Edgerton, M. E., Fisher, D. H., Tang, L., & Chen, Z. (2005) Using Prior Knowledge and Rule Induction Methods to Discover Molecular Markers of Prognosis in Lung Cancer. American Medical Informatics Association Symposium (Washington, DC).

    Technical Reports (selected)

    Fisher, D. (1985). "A Hierarchical Conceptual Clustering Algorithm," Technical Report 85-21, Department of Information and Computer Science, University of California, Irvine.

    Langley, P., Simon, H., Zytkow, J., & Fisher, D. (1985). "Discovering Qualitative Empirical Laws," Technical Report 85-18, Department of Information and Computer Science, University of California, Irvine.

    Fisher, D. (1987). "Knowledge Acquisition Via Incremental Conceptual Clustering," Technical Report 87-22 (Doctoral Dissertation), Department of Information and Computer Science, University of California, Irvine.

    Fisher, D., & Schlimmer, J. (1988). "Models of Incremental Concept Learning," Technical Report 88-05, Department of Computer Science, Vanderbilt University, Nashville, TN.

    One of 24 coauthors. (1991). "The MONK Problems -- A Performance Comparison of Different Learning Algorithms" CMU Technical Report CS-91-197, Department of Computer Science, CMU, Pittsburgh, PA.

    Fisher, D. (1992). Pessimistic and Optimistic Induction (TR CS-92-12).


    Douglas H. Fisher