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Learning Theory

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Produktnummer: 180afd0069c6a247afb8fca4f5e6090ecd
Themengebiete: Boosting Support Vector Machine algorithm analysis and problem complexity classification game theory learning learning theory supervised learning unsupervised learning
Veröffentlichungsdatum: 20.06.2005
EAN: 9783540265566
Sprache: Englisch
Seitenzahl: 692
Produktart: Kartoniert / Broschiert
Herausgeber: Auer, Peter Meir, Ron
Verlag: Springer Berlin
Untertitel: 18th Annual Conference on Learning Theory, COLT 2005, Bertinoro, Italy, June 27-30, 2005, Proceedings
Produktinformationen "Learning Theory"
This volume contains papers presented at the Eighteenth Annual Conference on Learning Theory (previously known as the Conference on Computational Learning Theory) held in Bertinoro, Italy from June 27 to 30, 2005. The technical program contained 45 papers selected from 120 submissions, 3 open problems selected from among 5 contributed, and 2 invited lectures. The invited lectures were given by Sergiu Hart on “Uncoupled Dynamics and Nash Equilibrium”, and by Satinder Singh on “Rethinking State, Action, and Reward in Reinforcement Learning”. These papers were not included in this volume. The Mark Fulk Award is presented annually for the best paper co-authored by a student. The student selected this year was Hadi Salmasian for the paper titled “The Spectral Method for General Mixture Models” co-authored with Ravindran Kannan and Santosh Vempala. The number of papers submitted to COLT this year was exceptionally high. In addition to the classical COLT topics, we found an increase in the number of submissions related to novel classi?cation scenarios such as ranking. This - crease re?ects a healthy shift towards more structured classi?cation problems, which are becoming increasingly relevant to practitioners.

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