Algorithmic Learning Theory (Record no. 188121)
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| fixed length control field | 06271nam a22006135i 4500 |
| 001 - CONTROL NUMBER | |
| control field | 978-3-540-49730-1 |
| 003 - CONTROL NUMBER IDENTIFIER | |
| control field | DE-He213 |
| 005 - DATE AND TIME OF LATEST TRANSACTION | |
| control field | 20240423132454.0 |
| 007 - PHYSICAL DESCRIPTION FIXED FIELD--GENERAL INFORMATION | |
| fixed length control field | cr nn 008mamaa |
| 008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION | |
| fixed length control field | 121227s1998 gw | s |||| 0|eng d |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER | |
| International Standard Book Number | 9783540497301 |
| -- | 978-3-540-49730-1 |
| 024 7# - OTHER STANDARD IDENTIFIER | |
| Standard number or code | 10.1007/3-540-49730-7 |
| Source of number or code | doi |
| 050 #4 - LIBRARY OF CONGRESS CALL NUMBER | |
| Classification number | QA75.5-76.95 |
| 072 #7 - SUBJECT CATEGORY CODE | |
| Subject category code | UYA |
| Source | bicssc |
| 072 #7 - SUBJECT CATEGORY CODE | |
| Subject category code | COM014000 |
| Source | bisacsh |
| 072 #7 - SUBJECT CATEGORY CODE | |
| Subject category code | UYA |
| Source | thema |
| 082 04 - DEWEY DECIMAL CLASSIFICATION NUMBER | |
| Classification number | 004.0151 |
| Edition number | 23 |
| 245 10 - TITLE STATEMENT | |
| Title | Algorithmic Learning Theory |
| Medium | [electronic resource] : |
| Remainder of title | 9th International Conference, ALT’98, Otzenhausen, Germany, October 8–10, 1998 Proceedings / |
| Statement of responsibility, etc | edited by Michael M. Richter, Carl H. Smith, Rolf Wiehagen, Thomas Zeugmann. |
| 250 ## - EDITION STATEMENT | |
| Edition statement | 1st ed. 1998. |
| 264 #1 - | |
| -- | Berlin, Heidelberg : |
| -- | Springer Berlin Heidelberg : |
| -- | Imprint: Springer, |
| -- | 1998. |
| 300 ## - PHYSICAL DESCRIPTION | |
| Extent | XI, 444 p. 1 illus. |
| Other physical details | online resource. |
| 336 ## - | |
| -- | text |
| -- | txt |
| -- | rdacontent |
| 337 ## - | |
| -- | computer |
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| -- | rdamedia |
| 338 ## - | |
| -- | online resource |
| -- | cr |
| -- | rdacarrier |
| 347 ## - | |
| -- | text file |
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| -- | rda |
| 490 1# - SERIES STATEMENT | |
| Series statement | Lecture Notes in Artificial Intelligence, |
| International Standard Serial Number | 2945-9141 ; |
| Volume number/sequential designation | 1501 |
| 505 0# - FORMATTED CONTENTS NOTE | |
| Formatted contents note | Editors’ Introduction -- Editors’ Introduction -- Inductive Logic Programming and Data Mining -- Scalability Issues in Inductive Logic Programming -- Inductive Inference -- Learning to Win Process-Control Games Watching Game-Masters -- Closedness Properties in EX-Identification of Recursive Functions -- Learning via Queries -- Lower Bounds for the Complexity of Learning Half-Spaces with Membership Queries -- Cryptographic Limitations on Parallelizing Membership and Equivalence Queries with Applications to Random Self-Reductions -- Learning Unary Output Two-Tape Automata from Multiplicity and Equivalence Queries -- Computational Aspects of Parallel Attribute-Efficient Learning -- PAC Learning from Positive Statistical Queries -- Prediction Algorithns -- Structured Weight-Based Prediction Algorithms -- Inductive Logic Programming -- Learning from Entailment of Logic Programs with Local Variables -- Logical Aspects of Several Bottom-Up Fittings -- Learnability of Translations from Positive Examples -- Analysis of Case-Based Representability of Boolean Functions by Monotone Theory -- Learning Formal Languages -- Locality, Reversibility, and Beyond: Learning Languages from Positive Data -- Synthesizing Learners Tolerating Computable Noisy Data -- Characteristic Sets for Unions of Regular Pattern Languages and Compactness -- Finding a One-Variable Pattern from Incomplete Data -- A Fast Algorithm for Discovering Optimal String Patterns in Large Text Databases -- Inductive Inference -- A Comparison of Identification Criteria for Inductive Inference of Recursive Real-Valued Functions -- Predictive Learning Models for Concept Drift -- Learning with Refutation -- Comparing the Power of Probabilistic Learning and Oracle Identification Under Monotonicity Constraints -- Learning Algebraic Structures from TextUsing Semantical Knowledge -- Inductive Logic Programming -- Lime: A System for Learning Relations -- Miscellaneous -- On the Sample Complexity for Neural Trees -- Learning Sub-classes of Monotone DNF on the Uniform Distribution -- Using Attribute Grammars for Description of Inductive Inference Search Space -- Towards the Validation of Inductive Learning Systems -- Consistent Polynomial Identification in the Limit. |
| 520 ## - SUMMARY, ETC. | |
| Summary, etc | This volume contains all the papers presented at the Ninth International Con- rence on Algorithmic Learning Theory (ALT’98), held at the European education centre Europ¨aisches Bildungszentrum (ebz) Otzenhausen, Germany, October 8{ 10, 1998. The Conference was sponsored by the Japanese Society for Arti cial Intelligence (JSAI) and the University of Kaiserslautern. Thirty-four papers on all aspects of algorithmic learning theory and related areas were submitted, all electronically. Twenty-six papers were accepted by the program committee based on originality, quality, and relevance to the theory of machine learning. Additionally, three invited talks presented by Akira Maruoka of Tohoku University, Arun Sharma of the University of New South Wales, and Stefan Wrobel from GMD, respectively, were featured at the conference. We would like to express our sincere gratitude to our invited speakers for sharing with us their insights on new and exciting developments in their areas of research. This conference is the ninth in a series of annual meetings established in 1990. The ALT series focuses on all areas related to algorithmic learning theory including (but not limited to): the theory of machine learning, the design and analysis of learning algorithms, computational logic of/for machine discovery, inductive inference of recursive functions and recursively enumerable languages, learning via queries, learning by arti cial and biological neural networks, pattern recognition, learning by analogy, statistical learning, Bayesian/MDL estimation, inductive logic programming, robotics, application of learning to databases, and gene analyses. |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical term or geographic name as entry element | Computer science. |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical term or geographic name as entry element | Artificial intelligence. |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical term or geographic name as entry element | Machine theory. |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical term or geographic name as entry element | Algorithms. |
| 650 14 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical term or geographic name as entry element | Theory of Computation. |
| 650 24 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical term or geographic name as entry element | Artificial Intelligence. |
| 650 24 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical term or geographic name as entry element | Formal Languages and Automata Theory. |
| 650 24 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical term or geographic name as entry element | Algorithms. |
| 700 1# - ADDED ENTRY--PERSONAL NAME | |
| Personal name | Richter, Michael M. |
| Relator term | editor. |
| Relator code | edt |
| -- | http://id.loc.gov/vocabulary/relators/edt |
| 700 1# - ADDED ENTRY--PERSONAL NAME | |
| Personal name | Smith, Carl H. |
| Relator term | editor. |
| Relator code | edt |
| -- | http://id.loc.gov/vocabulary/relators/edt |
| 700 1# - ADDED ENTRY--PERSONAL NAME | |
| Personal name | Wiehagen, Rolf. |
| Relator term | editor. |
| Relator code | edt |
| -- | http://id.loc.gov/vocabulary/relators/edt |
| 700 1# - ADDED ENTRY--PERSONAL NAME | |
| Personal name | Zeugmann, Thomas. |
| Relator term | editor. |
| Relator code | edt |
| -- | http://id.loc.gov/vocabulary/relators/edt |
| 710 2# - ADDED ENTRY--CORPORATE NAME | |
| Corporate name or jurisdiction name as entry element | SpringerLink (Online service) |
| 773 0# - HOST ITEM ENTRY | |
| Title | Springer Nature eBook |
| 776 08 - ADDITIONAL PHYSICAL FORM ENTRY | |
| Display text | Printed edition: |
| International Standard Book Number | 9783540650133 |
| 776 08 - ADDITIONAL PHYSICAL FORM ENTRY | |
| Display text | Printed edition: |
| International Standard Book Number | 9783662164655 |
| 830 #0 - SERIES ADDED ENTRY--UNIFORM TITLE | |
| Uniform title | Lecture Notes in Artificial Intelligence, |
| -- | 2945-9141 ; |
| Volume number/sequential designation | 1501 |
| 856 40 - ELECTRONIC LOCATION AND ACCESS | |
| Uniform Resource Identifier | <a href="https://doi.org/10.1007/3-540-49730-7">https://doi.org/10.1007/3-540-49730-7</a> |
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| 942 ## - ADDED ENTRY ELEMENTS (KOHA) | |
| Koha item type | eBooks-CSE-Springer |
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