Learning Theory

This volume contains papers presented at the 17th Annual Conference on Le- ning Theory (previously known as the Conference on Computational Learning Theory) held in Ban?, Canada from July 1 to 4, 2004. The technical program contained 43 papers selected from 107 submissions, 3 open problems selected from among 6 contributed, and 3 invited lectures. The invited lectures were given by Michael Kearns on -Game Theory, Automated Trading and Social Networks-, Moses Charikar on -Algorithmic Aspects of - nite Metric Spaces-, and Stephen Boyd on -Convex Optimization, Semide?nite Programming, and Recent Applications-. These papers were not included in this volume. The Mark Fulk Award is presented annually for the best paper co-authored by a student. Thisyear theMark Fulk award wassupplemented with two further awards funded by the Machine Learning Journal and the National Information Communication Technology Centre, Australia (NICTA). We were therefore able toselectthreestudentpapersforprizes.ThestudentsselectedwereMagalieF- montforthesingle-authorpaper-ModelSelectionbyBootstrapPenalizationfor Classi?cation-, Daniel Reidenbach for the single-author paper -On the Lear- bility of E-Pattern Languages over Small Alphabets-, and Ran Gilad-Bachrach for the paper -Bayes and Tukey Meet at the Center Point- (co-authored with Amir Navot and Naftali Tishby).