Algorithmic Learning Theory

by Nicolo Cesa-Bianchi (Editor), Rüdiger Reischuk (Editor), Masayuki Numao (Editor)

This volume contains the papers presented at the 13th Annual Conference on Algorithmic Learning Theory (ALT 2002), which was held in Lub ¨ eck (Germany) during November 24–26, 2002. The main objective of the conference was to p- vide an interdisciplinary forum discussing the theoretical foundations of machine learning as well as their relevance to practical applications. The conference was colocated with the Fifth International Conference on Discovery Science (DS 2002). The volume includes 26 technical contributions which were selected by the program committee from 49 submissions. It also contains the ALT 2002 invited talks presented by Susumu Hayashi (Kobe University, Japan) on “Mathematics Based on Learning”, by John Shawe-Taylor (Royal Holloway University of L- don, UK) on “On the Eigenspectrum of the Gram Matrix and Its Relationship to the Operator Eigenspectrum”, and by Ian H. Witten (University of Waikato, New Zealand) on “Learning Structure from Sequences, with Applications in a Digital Library” (joint invited talk with DS 2002). Furthermore, this volume - cludes abstracts of the invited talks for DS 2002 presented by Gerhard Widmer (Austrian Research Institute for Arti?cial Intelligence, Vienna) on “In Search of the Horowitz Interim Report on a Musical Discovery Project” and by Rudolf Kruse (University of Magdeburg, Germany) on “Data Mining with Graphical Models”. The complete versions of these papers are published in the DS 2002 proceedings (Lecture Notes in Arti?cial Intelligence, Vol. 2534). ALT has been awarding the E.

432 pages, Paperback

First published January 1, 2002