Resources

January 16, 2013

Surveys on Language Learning:

  1. Thomas Zeugmann and Steffen Lange, A Guided Tour Across the Boundaries of Learning Recursive Languages, in “Algorithmic Learning for Knowledge-Based Systems” (K.P. Jantke and S. Lange, Eds.), Lecture Notes in Artificial Intelligence 961, pp. 190 – 258, Springer-Verlag 1995.
  2. Steffen Lange, Thomas Zeugmann, and Sandra Zilles, Learning indexed families of recursive languages from positive data: A survey. Theoretical Computer Science, 397(1-3): 194-232, 2008.

Fundamental Papers:

  1. Ray Solomonoff, A formal theory of inductive inference. Part I. Information and Control, 7(1): 1-22, 1964.
  2. Ray Solomonoff , A formal theory of inductive inference. Part II. Information and Control, 7(2): 224-254, 1964.
  3. Hillary Putnam, Trial and error predicates and the solution to a problem of Mostowski. The Journal of Symbolic Logic, 30 (1): 49-57, 1965.
  4. E. Mark Gold, Language identification in the limit. Information and Control 10: 447-474, 1967.

Additional Topics:

  1. Dana Angluin, Computational learning theory: survey and selected bibliography, in Annual ACM Symposium on Theory of Computing, Proceedings of the twenty-fourth annual ACM symposium on Theory of computing, Victoria, British Columbia, Canada, pp. 351 – 369, 1992.
  2. Ricard Gavaldà, The Complexity of Learning with Queries, Proceedings of the 9th IEEE Structures in Complexity Theory Conference, IEEE Press, 324-337, 1994.
  3. Martin Anthony, Probabilistic Analysis of Learning in Artificial Neural Networks: The PAC Model and its Variants, Neural Computing Surveys, Vol.1, 1-47, 1997.
  4. William Gasarch and Carl H. Smith, A survey of inductive inference with an emphasis on queries, in Complexity, Logic, and Recursion Theory, (A. Sorbi, Ed.), Lecture Notes in Pure and Applied Mathematics, Volume 187, pp. 225-260, Marcel Dekker, Inc., New York, USA, 1997.
  5. Olivier Bousquet, Stéphane Boucheron and Gábor Lugosi, Introduction to Statistical Learning Theory, in “Advanced Lectures on Machine Learning”, (Olivier Bousquet, Ulrike von Luxburg, and Gunnar Rätsch, Eds.), Lecture Notes in Artificial Intelligence 3176, pp. 169 – 207, 2004.
  6. Thomas Zeugmann and Sandra Zilles, Learning Recursive Functions. A survey. Theoretical Computer Science 397: 4–56, 2008.
  7. Yasuhito Mukouchi, Characterization of Finite IdentificationAII 1992: 260-267, 1992.