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

This volume contains the papers presented at the 12th Annual Conference on Algorithmic Learning Theory (ALT 2001), which was held in Washington DC, USA, during November 25–28, 2001. The main objective of the conference is to provide an inter-disciplinary forum for the discussion of theoretical found...

Full description

Bibliographic Details
Other Authors: Abe, Naoki (Editor), Khardon, Roni (Editor), Zeugmann, Thomas (Editor)
Format: eBook
Language:English
Published: Berlin, Heidelberg Springer Berlin Heidelberg 2001, 2001
Edition:1st ed. 2001
Series:Lecture Notes in Artificial Intelligence
Subjects:
Online Access:
Collection: Springer Book Archives -2004 - Collection details see MPG.ReNa
Table of Contents:
  • 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