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Algorithmic Learning Theory : 14th International Conference, ALT 2003, Sapporo, Japan, October 17-19, 2003, Proceedings - Ricard Gavalda

Algorithmic Learning Theory

14th International Conference, ALT 2003, Sapporo, Japan, October 17-19, 2003, Proceedings

By: Ricard Gavalda (Editor), Klaus P. Jantke (Editor), Eiji Takimoto (Editor)


Published: 7th October 2003
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This volume contains the papers presented at the 14th Annual Conference on Algorithmic Learning Theory (ALT 2003), which was held in Sapporo (Japan) duringOctober17-19,2003. Themainobjectiveoftheconferencewastoprovide an interdisciplinary forum for discussing the theoretical foundations of machine learning as well as their relevance to practical applications. The conference was co-locatedwiththe6thInternationalConferenceonDiscoveryScience(DS2003). The volume includes 19 technical contributions that were selected by the program committee from 37 submissions. It also contains the ALT 2003 invited talks presented by Naftali Tishby (Hebrew University, Israel) on "E?cient Data Representations that Preserve Information," by Thomas Zeugmann (University of Lub ] eck, Germany) on "Can Learning in the Limit be Done E?ciently?," and by Genshiro Kitagawa (Institute of Statistical Mathematics, Japan) on "S- nal Extraction and Knowledge Discovery Based on Statistical Modeling" (joint invited talk with DS 2003). Furthermore, this volume includes abstracts of the invitedtalksforDS2003presentedbyThomasEiter(ViennaUniversityofTe- nology, Austria) on "Abduction and the Dualization Problem" and by Akihiko Takano (National Institute of Informatics, Japan) on "Association Computation for Information Access. " The complete versions of these papers were published in the DS 2003 proceedings (Lecture Notes in Arti?cial Intelligence Vol. 2843). ALT has been awarding theE. MarkGoldAward for the most outstanding paper by a student author since 1999. This year the award was given to Sandra Zilles for her paper "Intrinsic Complexity of Uniform Learning. " This conference was the 14th in a series of annual conferences established in 1990. ContinuationoftheALTseriesissupervisedbyitssteeringcommittee, c- sisting of: Thomas Zeugmann (Univ.

Abduction and the Dualization Problemp. 1
Signal Extraction and Knowledge Discovery Based on Statistical Modelingp. 3
Association Computation for Information Accessp. 15
Efficient Data Representations That Preserve Informationp. 16
Can Learning in the Limit Be Done Efficiently?p. 17
Intrinsic Complexity of Uniform Learningp. 39
On Ordinal VC-Dimensional and Some Notions of Complexityp. 54
Learning of Erasing Primitive Formal Systems from Positive Examplesp. 69
Changing the Inference Type - Keeping the Hypothesis Spacep. 84
Robust Inference of Relevant Attributesp. 99
Efficient Learning of Ordered and Unordered Tree Patterns with Contractible Variablesp. 114
On the Learnability of Erasing Pattern Languages in the Query Modelp. 129
Learning of Finite Unions of Tree Patterns with Repeated Internal Structured Variables from Queriesp. 144
Kernel Trick Embedded Gaussian Mixture Modelp. 159
Efficiently Learning the Metric with Side-Informationp. 175
Learning Continuous Latent Variable Models with Bregman Divergencesp. 190
A Stochastic Gradient Descent Algorithm for Structural Risk Minimisationp. 205
On the Complexity of Training a Single Perceptron with Programmable Synaptic Delaysp. 221
Learning a Subclass of Regular Patterns in Polynomial Timep. 234
Identification with Probability One of Stochastic Deterministic Linear Languagesp. 247
Criterion of Calibration for Transductive Confidence Machine with Limited Feedbackp. 259
Well-Calibrated Predictions from Online Compression Modelsp. 268
Transductive Confidence Machine Is Universalp. 283
On the Existence and Convergence of Computable Universal Priorsp. 298
Author Indexp. 313
Table of Contents provided by Blackwell. All Rights Reserved.

ISBN: 9783540202912
ISBN-10: 3540202919
Series: Lecture Notes in Artificial Intelligence
Audience: Professional
Format: Paperback
Language: English
Number Of Pages: 320
Published: 7th October 2003
Publisher: Springer-Verlag Berlin and Heidelberg Gmbh & Co. Kg
Country of Publication: DE
Dimensions (cm): 23.3 x 15.5  x 1.75
Weight (kg): 1.03