Algorithmic Learning Theory算法学习理论/会议录

书籍目录

Editors' IntroductionInvited Papers  Invention and Artificial Intelligence  The Arrowsmith Project: 2005 Status Report  The Robot Scientist Project  Algorithms and Software for Collaborative Discovery from Autonomous, Semantically Heterogeneous, Distributed Information Sources  Training Support Vector Machines via SMO-Type Decomposition MethodsKernel-Based LearningRegular Contributions  Measuring Statistical Dependence with Hilbert-Schmidt Norms  An Analysis of the Anti-learning Phenomenon for the Class Symmetric PolyhedronBayesian and Statistical Models  Learning Causal Structures Based on Markov Equivalence Class  Stochastic Complexity for Mixture of Exponential Families in Variational Bayes  ACME: An Associative Classifier Based on Maximum Entropy PrinciplePAC-Learning  Constructing Multiclass Learners from Binary Learners:A Simple Black-Box Analysis of the Generalization Errors  On Computability of Pattern Recognition Problems  PAC-Learnability of Probabilistic Deterministic Finite State Automata in Terms of Variation Distance  Learnability of Probabilistic Automata via OraclesQuery-Learning  Learning Attribute-Efficiently with Corrupt Oracles  Learning DNF by Statistical and Proper Distance Queries Under the Uniform Distribution  Learning of Elementary Formal Systems with Two Clauses Using Queries  Gold-Style and Query Learning Under Various Constraints on the Target ClassInductive Inference  Non U-Shaped Vacillatory and Team Learning  Learning Multiple Languages in GroupsLanguage Learning Learning and LogicLearning from Expert AdviceOnline LearningDefensive ForecastingTeachingAuthor Index

作者简介

This book constitutes the refereed proceedings of the 16th International Conference on Algorithmic Learning Theory, ALT 2005, held in Singapore in October 2005. The 30 revised full papers presented together with 5 invited papers and an introduction by the editors were carefully reviewed and selected from 98 submissions. The papers are organized in topical sections on kernel-based learning, bayesian and statistical models, PAC-learning, query-learning, inductive inference, language learning, learning and logic, learning from expert advice, online learning, defensive forecasting, and teaching.

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