19th International Conference on Algorithmic Learning Theory, ALT 2008, Proceedings (2008)
Freund, Y., Gyorfi, Laszlo, Turán, Gy., Zeugmann, T.
This volume contains papers presented at the 19th International Conference on Algorithmic Learning Theory (ALT 2008), which was held in Budapest, Hungary during October 13–16, 2008. The conference...
Nonparametric Independence Tests: Space Partitioning and Kernel Approaches (2008)
Gretton, A., Györfi, L., Freund, Y., Györfi, L., Turán, G., Zeugmann, T.
Three simple and explicit procedures for testing the independence of two multi-dimensional random variables are described. Two of the associated test statistics (L1, log-likelihood) are defined when...
Refutable Inductive Inference of Recursive Functions (2007)
S. Jain, E. Kinber, R. Wiehagen, T. Zeugmann, Serie A, Sanjay Jain, ...
Learning of recursive functions refutably informally means that for every recursive function, the learning machine has either to learn this function or to refute it, that is to signal that it is not...
N-gram Analysis Based on Zero-suppressed BDDs (2006)
R. Kurai, S. Minato, T. Zeugmann, Ryutaro Kurai, Shin-ichi Minato, Thomas Zeugmann
In present paper, we propose a new method of n-gram analysis using ZB-DDs (Zero-suppressed BDDs). ZBDDs are known as a compact representation of combinatorial item sets. Here, we newly apply the...
Incremental Concept Learning for Bounded Data Mining (1997)
J. Case, S. Jain, S. Lange, T. Zeugmann, Sanjay Jain, Steffen Lange, ...
Important refinements of concept learning in the limit from positive data considerably restricting the accessibility of input data are studied. Let c be any concept; every infinite sequence of...