![Ben David, Shai / Akira Maruoka et al (Hrsg.). Algorithmic Learning Theory - 15th International Conference, ALT 2004, Padova, Italy, October 2-5, 2004. Proceedings. Springer Berlin Heidelberg, 2004.](https://eichendorff21.de/cdata/T6cEYIh3Tq5SPVvnF-MRGB1ojYE=/300x0/9783540233565.png)
Algorithmic Learning Theory
- Springer Berlin Heidelberg
- 2004
- Taschenbuch
- 528 Seiten
- ISBN 9783540233565
Algorithmic learning theory is mathematics about computer programs which learn from experience. This involves considerable interaction between various mathematical disciplines including theory of computation, statistics, and c- binatorics. There is also considerable interaction with the practical, empirical ?elds of machine and statistical learning in which a principal aim is to predict, from past data about phenomena, useful features of future data from the same phenomena. The papers in this volume cover a broad range of topics of current research in the ?eld of algorithmic learning theory. We have divided the 29 technical, contributed papers in this volume into eight categories (corresponding to eight sessions) re?ecting this
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