Learning Theory 17th Annual Conference on Learning Theory, COLT 2004, Banff, Canada, July 1-4, 2004, Proceedings

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).

Dettagli sul prodotto

• Con la collaborazione di: John Shawe-Taylor (Editore), Singer (Editore), Yoram Singer (Editore), Singer (Editore), Joh Shawe-Taylor (Editore)
• Editore: Springer, Berlin
• Lingue: Inglese
• Contenuto: Libro
• Forma del prodotto: Tascabile
• Data pubblicazione: 23.08.2005
• Categoria: Scienze naturali, medicina, informatica, tecnica > Informatica, EDP > Informatica
• EAN: 9783540222828
• ISBN: 978-3-540-22282-8
• Numero di pagine: 654
• Illustrazioni: X, 654 p.
• Altezza (della confezione): 23.5 cm
• Peso (della confezione): 920 g
• Serie: Lecture Notes in Computer Science > 3120; Lecture Notes in Artificial Intelligence; Lecture Notes in Computer Science; Lecture Notes in Artificial Intelligence
• Categorie: C, Algorithmen und Datenstrukturen, Algorithms, Artificial Intelligence, Theoretische Informatik, computer science, Theory of Computation, Computers, Algorithms & data structures, Mathematical theory of computation, Algorithm Analysis and Problem Complexity, Mathematical logic, Statistical Learning, Mathematical Logic and Formal Languages, Computation by Abstract Devices, Formal Languages and Automata Theory, support vector machine, Online Learning