Algorithmic Learning Theory: 14th International Conference, Alt 2003, Sapporo, Japan, October 17-19, 2003, Proceedings: 14th Int by Ricard GavaldAlgorithmic Learning Theory: 14th International Conference, Alt 2003, Sapporo, Japan, October 17-19, 2003, Proceedings: 14th Int by Ricard Gavald

Algorithmic Learning Theory: 14th International Conference, Alt 2003, Sapporo, Japan, October 17-19…

byRicard GavaldEditorKlaus P. Jantke, Eiji Takimoto

Paperback | October 7, 2003

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ContinuationoftheALTseriesissupervisedbyitssteeringcommittee,c- sisting of: Thomas Zeugmann (Univ.
Title:Algorithmic Learning Theory: 14th International Conference, Alt 2003, Sapporo, Japan, October 17-19…Format:PaperbackDimensions:320 pages, 23.3 × 15.5 × 0.01 inPublished:October 7, 2003Publisher:Springer-Verlag/Sci-Tech/TradeLanguage:English

The following ISBNs are associated with this title:

ISBN - 10:3540202919

ISBN - 13:9783540202912

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Table of Contents

Invited Papers.- Abduction and the Dualization Problem.- Signal Extraction and Knowledge Discovery Based on Statistical Modeling.- Association Computation for Information Access.- Efficient Data Representations That Preserve Information.- Can Learning in the Limit Be Done Efficiently?.- Inductive Inference.- Intrinsic Complexity of Uniform Learning.- On Ordinal VC-Dimension and Some Notions of Complexity.- Learning of Erasing Primitive Formal Systems from Positive Examples.- Changing the Inference Type - Keeping the Hypothesis Space.- Learning and Information Extraction.- Robust Inference of Relevant Attributes.- Efficient Learning of Ordered and Unordered Tree Patterns with Contractible Variables.- Learning with Queries.- On the Learnability of Erasing Pattern Languages in the Query Model.- Learning of Finite Unions of Tree Patterns with Repeated Internal Structured Variables from Queries.- Learning with Non-linear Optimization.- Kernel Trick Embedded Gaussian Mixture Model.- Efficiently Learning the Metric with Side-Information.- Learning Continuous Latent Variable Models with Bregman Divergences.- A Stochastic Gradient Descent Algorithm for Structural Risk Minimisation.- Learning from Random Examples.- On the Complexity of Training a Single Perceptron with Programmable Synaptic Delays.- Learning a Subclass of Regular Patterns in Polynomial Time.- Identification with Probability One of Stochastic Deterministic Linear Languages.- Online Prediction.- Criterion of Calibration for Transductive Confidence Machine with Limited Feedback.- Well-Calibrated Predictions from Online Compression Models.- Transductive Confidence Machine Is Universal.- On the Existence and Convergence of Computable Universal Priors.