Algorithmic Learning Theory

Editors' Introduction.- Editors' Introduction.- Invited Papers.- Towards General Algorithms for Grammatical Inference.- The Blessing and the Curse of the Multiplicative Updates.- Discovery of Abstract Concepts by a Robot.- Contrast Pattern Mining and Its Application for Building Robust Classifiers.- Optimal Online Prediction in Adversarial Environments.- Regular Contributions.- An Algorithm for Iterative Selection of Blocks of Features.- Bayesian Active Learning Using Arbitrary Binary Valued Queries.- Approximation Stability and Boosting.- A Spectral Approach for Probabilistic Grammatical Inference on Trees.- PageRank Optimization in Polynomial Time by Stochastic Shortest Path Reformulation.- Inferring Social Networks from Outbreaks.- Distribution-Dependent PAC-Bayes Priors.- PAC Learnability of a Concept Class under Non-atomic Measures: A Problem by Vidyasagar.- A PAC-Bayes Bound for Tailored Density Estimation.- Compressed Learning with Regular Concept.- A Lower Bound for Learning Distributions Generated by Probabilistic Automata.- Lower Bounds on Learning Random Structures with Statistical Queries.- Recursive Teaching Dimension, Learning Complexity, and Maximum Classes.- Toward a Classification of Finite Partial-Monitoring Games.- Switching Investments.- Prediction with Expert Advice under Discounted Loss.- A Regularization Approach to Metrical Task Systems.- Solutions to Open Questions for Non-U-Shaped Learning with Memory Limitations.- Learning without Coding.- Learning Figures with the Hausdorff Metric by Fractals.- Inductive Inference of Languages from Samplings.- Optimality Issues of Universal Greedy Agents with Static Priors.- Consistency of Feature Markov Processes.- Algorithms for Adversarial Bandit Problems with Multiple Plays.- Online Multiple Kernel Learning: Algorithms and Mistake Bounds.- An Identity for Kernel Ridge Regression.