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  • Editorial : exploratory research in machine learning

    Creator:
    Dietterich, Thomas G.
    Abstract:
    Exploratory research contributes to the continued vitality of every discipline. The aim of exploratory research is to identify new tasks-tasks that cannot be solved by existing methods. Once a new task has been found, exploratory research seeks to develop a precise definition of the task and to understand the factors...
    Resource Type:
    Technical Report
    Full Text:
    International Joint Conference on Artificial Intelligence (pp. 788-793) . Detroit, MI: Morgan Kaufmann. Hunt

  • Varieties of operationality

    Creator:
    Dietterich, Thomas G. and Bennett, James S.
    Abstract:
    In recent papers on machine learning, the term 'operationalization' has been used to describe the purpose of the learning process. In particular, explanation-based learning systems are said to 'operationalize' the given target concept. Unfortunately, the exact meaning of this term has varied from one paper to another, and frequently the...
    Resource Type:
    Technical Report
    Full Text:
    Spring Symposium on Explanation- Based Learning, when he asked the audience if there were any factors

  • A study of explanation-based methods for inductive learning

    Creator:
    Flann, Nicholas S. and Dietterich, Thomas G.
    Abstract:
    This paper formalizes a new learning from examples problem: identifying a correct concept definition from positive examples such that the concept is some specialization of a target concept defined by a domain theory. This paper describes an empirical study that evaluates three methods for solving this problem: explanation based generalization...
    Resource Type:
    Technical Report

  • On learning more concepts

    Creator:
    Almuallim, Hussein and Dietterich, Thomas G.
    Abstract:
    The coverage of a learning algorithm is the number of concepts that can be learned by that algorithm from samples of a given size. This paper asks whether good learning algorithms can be designed by maximizing their coverage. The paper extends a previous upper bound on the coverage of any...
    Resource Type:
    Technical Report
    Full Text:
    Proceedings of the Sixth International Conference on Machine Learning, 124-128. Ithaca, NY: Morgan Kaufmann

  • Learning at the knowledge level

    Creator:
    Dietterich, Thomas G.
    Abstract:
    When Newell introduced the concept of the knowledge level as a useful level of description for computer systems, he focused on the representation of knowl­edge. This paper applies the knowledge level notion to the problem of knowl­edge acquisition. Two interesting issues arise. First, some existing machine learning programs appear to...
    Resource Type:
    Technical Report