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

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  • Formāts: PDF+DRM
  • Sērija : Lecture Notes in Artificial Intelligence 2225
  • Izdošanas datums: 30-Jun-2003
  • Izdevniecība: Springer-Verlag Berlin and Heidelberg GmbH & Co. K
  • Valoda: eng
  • ISBN-13: 9783540455837
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Algorithmic Learning Theory: 12th International Conference, ALT 2001, Washington, DC, USA, November 25-28, 2001. Proceedings.Palielināt
  • Formāts: PDF+DRM
  • Sērija : Lecture Notes in Artificial Intelligence 2225
  • Izdošanas datums: 30-Jun-2003
  • Izdevniecība: Springer-Verlag Berlin and Heidelberg GmbH & Co. K
  • Valoda: eng
  • ISBN-13: 9783540455837
Citas grāmatas par šo tēmu:

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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 foundations of machine learning, as well as their relevance to practical applications. The conference was co-located with the Fourth International Conference on Discovery Science (DS 2001). The volume includes 21 contributed papers. These papers were selected by the program committee from 42 submissions based on clarity, signi cance, o- ginality, and relevance to theory and practice of machine learning. Additionally, the volume contains the invited talks of ALT 2001 presented by Dana Angluin of Yale University, USA, Paul R. Cohen of the University of Massachusetts at Amherst, USA, and the joint invited talk for ALT 2001 and DS 2001 presented by Setsuo Arikawa of Kyushu University, Japan. Furthermore, this volume includes abstracts of the invited talks for DS 2001 presented by Lindley Darden and Ben Shneiderman both of the University of Maryland at College Park, USA. The complete versions of these papers are published in the DS 2001 proceedings (Lecture Notes in Arti cial Intelligence Vol. 2226).

Papildus informācija

Springer Book Archives
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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