Selected publications

Journals

• Reidenbach, D., Schneider, J.C.,
  Morphically Primitive Words. Theoretical Computer Science 410 (2009) 2148-2161.

• Freydenberger, D.D., Reidenbach, D., Schneider, J.C.,
  Unambiguous Morphic Images of Strings. International Journal of Foundations of Computer Science 17 (2006) 601-628.
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• Reidenbach, D.,
  A non-learnable class of E-pattern languages. Theoretical Computer Science 350 (2006) 91-102.
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• Case, J., Jain, S., Stephan, F., Wiehagen, R.,
  Robust learning - rich and poor. Journal of Computer and System Sciences 69 (2004) 123-165.
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• Jain, S., Kinber, E., Wiehagen, R.,
  Learning all subfunctions of a function. Information and Computation 192 (2004) 185-215.
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• Lange, S., Zilles, S.,
  Formal language identification: query learning vs. Gold-style learning. Information Processing Letters 91 (2004) 285-292.
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• Zilles, S.,
  Separation of uniform learning classes. Theoretical Computer Science 313 (2004) 229-265.
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• Jain, S., Kinber, E., Papazian, C., Smith, C., Wiehagen, R.,
  On the intrinsic complexity of learning recursive functions. Information and Computation 184 (2003) 45-70.
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• Jain, S., Kinber, E., Wiehagen, R., Zeugmann, Th.,
  On learning of functions refutably. Theoretical Computer Science 298 (2003) 111-143.
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• Freivalds, R., Karpinski, M., Smith, C.H., Wiehagen, R.,
  Learning by the process of elimination. Information and Computation 176 (2002) 37-50.
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• Jain, S., Kinber, E., Wiehagen, R.,
  Language learning from texts: Degrees of intrinsic complexity and their characterizations. Journal of Computer and System Sciences 63 (2001) 305-354.
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• Jain, S., Nessel, J.,
  Some independence results for control structures in complete numberings. Journal of Symbolic Logic 66 (2001) 357-382.
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• Jain, S., Lange, S., Nessel, J.,
  On the learnabilitiy of recursively enumerable languages from good examples. Theoretical Computer Science 261 (2001) 3-29.
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• Jain, S., Smith, C., Wiehagen, R.,
  Robust learning is rich. Journal of Computer and System Sciences 62 (2001) 178-212.
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• Kurtz, S.A., Smith, C.H., Wiehagen, R.,
  On the role of search for learning from examples. Journal of Experimental and Theoretical Artificial Intelligence 13 (2001) 25-43.
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• Wiehagen, R., Zeugmann, T., Eds.,
  Algorithmic Learning Theory. Theoretical Computer Science 268 (2001) 175-393.
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• Jain, S., Kinber, E., Lange, S., Wiehagen, R., Zeugmann, Th.,
  Learning languages and functions by erasing. Theoretical Computer Science 241 (2000) 143-189.
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• Freivalds, R., Botuscharov, O., Wiehagen, R.,
  Identifying nearly minimal Gödel numbers from additional information. Annals of Mathematics and Artificial Intelligence 23 (1998) 199-209.
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• Lange, S., Nessel, J., Wiehagen, R.,
  Learning recursive languages from good examples. Annals of Mathematics and Artificial Intelligence 23 (1998) 27-52.
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• Smith, C.H., Wiehagen, R., Zeugmann, Th.,
  Classifying predicates and languages. International Journal of Foundations of Computer Science 8 (1997) 15-41.
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• Freivalds, R., Kinber, E.B., Wiehagen, R.,
  How inductive inference strategies discover their errors. Information and Computation 118 (1995) 208-226.
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• Kinber, E., Smith, C.H., Velauthapillai, M., Wiehagen, R.,
  On learning multiple concepts in parallel. Journal of Computer and System Sciences 50 (1995) 41-52.
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• Wiehagen, R., Smith, C.H.,
  Classification versus generalization. Journal of Experimental and Theoretical Artificial Intellgence 7 (1995) 163-174.
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• Wiehagen, R.,
  From inductive inference to algorithmic learning theory. New Generation Computing 12 (1994) 321-335.
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• Wiehagen, R., Zeugmann, T.,
  Ignoring data may be the only way to learn efficiently. Journal of Experimental and Theoretical Artificial Intelligence 6 (1994) 131-144.
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• Freivalds, R., Kinber, E.B., Wiehagen, R.,
  On the power of inductive inference from good examples. Theoretical Computer Science 110 (1993) 131-144.