e-book Algorithmic Learning Theory: Third Workshop, ALT 92 Tokyo, Japan, October 20–22, 1992 Proceedings

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Apprentissage automatique. Auteurs, contributeurs Kittler, Josef Date de publication 92 Jantke, Toyaki Nishida.

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Cohen, Haym Hirsh. Jantke, Takeshi Shinohara, Thomas Zeugmann. Bickhard, Loren Terveen. Mercer, Eric Neufeld.


  • Doshita, S. (Shuji) 1935-?
  • Algorithmic Learning Theory - ALT '92 : Shuji Doshita : .
  • Algorithmic Learning Theory - ALT '92.
  • OKUBO Yoshiaki!
  • US Hypersonic Research and Development: The Rise and Fall of Dyna-Soar, 1944-1963 (Space, Power & Politics Series).

Smith, Rolf Wiehagen, Thomas Zeugmann. Zighed, Ricco Rakotomalala. Vous allez obtenir un document que vous pourrez enregistrer ou imprimer. Envoyer par courriel. Exporter en CSV. Vous allez obtenir un document csv.


  1. Disaster Planning. Proceedings of a Symposium Held at the Royal Naval Hospital, Haslar, Gosport, Hants, on 10 and 11 October, 1974.
  2. Doshita, S. (Shuji) 1935-;
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    東京大学大学院情報理工学系研究科 数理情報学専攻 山西健司|プロフィール

    Haut de page. Data abstractions for decision tree induction. New Generation Comput. Books etc Plain Text. Search Algorithms and Applications. Web Intelligence and Intelligent Agents. Theory of Computation. Consideration on Finding Proper Maximal k-Plexes. A Framework of Associative Search by Mediators. Mining Contrast Concepts Representing Differences.

    This report discusses an effective depth-first mining algorithm for finding implicit crossover concepts connecting several major concepts. The algorithm is based on a dynamic ordering method depending on each search node and some search tree expan A PseudoFC can be viewed as a natural approximation of formal concepts.


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    It covers several formal concepts as its majorities and can work as a representative of them. In this paper, we are concerned with a problem of finding pseudo-cliques in a given graph G. A pseudo-clique is defined as the union of several maximal cliques in G with a required degree of overlap. Such a degree is determined by a user-defined p A Framework of Viewpoint-Based Clustering.