Algorithmic Learning Theory: 12th International Conference, ALT 2001, Washington, DC, USA, November 25-28, 2001. Proceedings. - Tapa blanda

Sinopsis

Editors' Introduction.- Editors' Introduction.- Invited Papers.- The Discovery Science Project in Japan.- Queries Revisited.- Robot Baby 2001.- Discovering Mechanisms: A Computational Philosophy of Science Perspective.- Inventing Discovery Tools: Combining Information Visualization with Data Mining.- Complexity of Learning.- On Learning Correlated Boolean Functions Using Statistical Queries (Extended Abstract).- A Simpler Analysis of the Multi-way Branching Decision Tree Boosting Algorithm.- Minimizing the Quadratic Training Error of a Sigmoid Neuron Is Hard.- Support Vector Machines.- Learning of Boolean Functions Using Support Vector Machines.- A Random Sampling Technique for Training Support Vector Machines.- New Learning Models.- Learning Coherent Concepts.- Learning Intermediate Concepts.- Real-Valued Multiple-Instance Learning with Queries.- Online Learning.- Loss Functions, Complexities, and the Legendre Transformation.- Non-linear Inequalities between Predictive and Kolmogorov Complexities.- Inductive Inference.- Learning by Switching Type of Information.- Learning How to Separate.- Learning Languages in a Union.- On the Comparison of Inductive Inference Criteria for Uniform Learning of Finite Classes.- Refutable Inductive Inference.- Refutable Language Learning with a Neighbor System.- Learning Recursive Functions Refutably.- Refuting Learning Revisited.- Learning Structures and Languages.- Efficient Learning of Semi-structured Data from Queries.- Extending Elementary Formal Systems.- Learning Regular Languages Using RFSA.- Inference of ?-Languages from Prefixes.

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