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04417nam a2200577 4500 |
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978-3-540-39624-6 |
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20191022112510.0 |
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121227s2003 gw | s |||| 0|eng d |
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|a 9783540396246
|9 978-3-540-39624-6
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|a 10.1007/b14273
|2 doi
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|d GrThAP
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|a Q334-342
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|a UYQ
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|a COM004000
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|a UYQ
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|a 006.3
|2 23
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|a Algorithmic Learning Theory
|h [electronic resource] :
|b 14th International Conference, ALT 2003, Sapporo, Japan, October 17-19, 2003, Proceedings /
|c edited by Ricard Gavaldà, Klaus P. Jantke, Eiji Takimoto.
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|a 1st ed. 2003.
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|a Berlin, Heidelberg :
|b Springer Berlin Heidelberg :
|b Imprint: Springer,
|c 2003.
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|a XII, 320 p.
|b online resource.
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|a text
|b txt
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|a computer
|b c
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|a online resource
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|a text file
|b PDF
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|a Lecture Notes in Artificial Intelligence ;
|v 2842
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|a 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.
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|a Artificial intelligence.
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|a Computers.
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|a Algorithms.
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|a Mathematical logic.
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|a Natural language processing (Computer science).
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1 |
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|a Artificial Intelligence.
|0 http://scigraph.springernature.com/things/product-market-codes/I21000
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|a Computation by Abstract Devices.
|0 http://scigraph.springernature.com/things/product-market-codes/I16013
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|a Algorithm Analysis and Problem Complexity.
|0 http://scigraph.springernature.com/things/product-market-codes/I16021
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2 |
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|a Mathematical Logic and Formal Languages.
|0 http://scigraph.springernature.com/things/product-market-codes/I16048
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|a Natural Language Processing (NLP).
|0 http://scigraph.springernature.com/things/product-market-codes/I21040
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1 |
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|a Gavaldà, Ricard.
|e editor.
|0 (orcid)0000-0003-4736-7179
|1 https://orcid.org/0000-0003-4736-7179
|4 edt
|4 http://id.loc.gov/vocabulary/relators/edt
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700 |
1 |
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|a Jantke, Klaus P.
|e editor.
|4 edt
|4 http://id.loc.gov/vocabulary/relators/edt
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700 |
1 |
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|a Takimoto, Eiji.
|e editor.
|4 edt
|4 http://id.loc.gov/vocabulary/relators/edt
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710 |
2 |
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|a SpringerLink (Online service)
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773 |
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|t Springer eBooks
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776 |
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|i Printed edition:
|z 9783662163023
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776 |
0 |
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|i Printed edition:
|z 9783540202912
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830 |
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|a Lecture Notes in Artificial Intelligence ;
|v 2842
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856 |
4 |
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|u https://doi.org/10.1007/b14273
|z Full Text via HEAL-Link
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912 |
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|a ZDB-2-SCS
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912 |
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|a ZDB-2-LNC
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912 |
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|a ZDB-2-BAE
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|a Computer Science (Springer-11645)
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