Algorithmic Learning Theory: 15th International Conference, ALT 2004, Padova, Italy, October 2-5, 2004. Proceedings - Softcover

Softcover

ISBN 10: 3662205203 ISBN 13: 9783662205204

Publisher: Springer, 2014

Synopsis

Invited Papers.- String Pattern Discovery.- Applications of Regularized Least Squares to Classification Problems.- Probabilistic Inductive Logic Programming.- Hidden Markov Modelling Techniques for Haplotype Analysis.- Learning, Logic, and Probability: A Unified View.- Regular Contributions.- Learning Languages from Positive Data and Negative Counterexamples.- Inductive Inference of Term Rewriting Systems from Positive Data.- On the Data Consumption Benefits of Accepting Increased Uncertainty.- Comparison of Query Learning and Gold-Style Learning in Dependence of the Hypothesis Space.- Learning r-of-k Functions by Boosting.- Boosting Based on Divide and Merge.- Learning Boolean Functions in AC 0 on Attribute and Classification Noise.- Decision Trees: More Theoretical Justification for Practical Algorithms.- Application of Classical Nonparametric Predictors to Learning Conditionally I.I.D. Data.- Complexity of Pattern Classes and Lipschitz Property.- On Kernels, Margins, and Low-Dimensional Mappings.- Estimation of the Data Region Using Extreme-Value Distributions.- Maximum Entropy Principle in Non-ordered Setting.- Universal Convergence of Semimeasures on Individual Random Sequences.- A Criterion for the Existence of Predictive Complexity for Binary Games.- Full Information Game with Gains and Losses.- Prediction with Expert Advice by Following the Perturbed Leader for General Weights.- On the Convergence Speed of MDL Predictions for Bernoulli Sequences.- Relative Loss Bounds and Polynomial-Time Predictions for the k-lms-net Algorithm.- On the Complexity of Working Set Selection.- Convergence of a Generalized Gradient Selection Approach for the Decomposition Method.- Newton Diagram and Stochastic Complexity in Mixture of Binomial Distributions.- Learnability of Relatively Quantified Generalized Formulas.- Learning Languages Generated by Elementary Formal Systems and Its Application to SH Languages.- New Revision Algorithms.- The Subsumption Lattice and Query Learning.- Learning of Ordered Tree Languages with Height-Bounded Variables Using Queries.- Learning Tree Languages from Positive Examples and Membership Queries.- Learning Content Sequencing in an Educational Environment According to Student Needs.- Tutorial Papers.- Statistical Learning in Digital Wireless Communications.- A BP-Based Algorithm for Performing Bayesian Inference in Large Perceptron-Type Networks.- Approximate Inference in Probabilistic Models.

Edition details

• Publisher: Springer
• Publication date: 2014
• Language: English
• ISBN 10: 3662205203
• ISBN 13: 9783662205204
• Binding: Paperback
• Number of pages: 528
• Editor: Ben David Shai, Case John, Maruoka Akira