E Book

Algorithmic Learning Theory

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Editors’ Introduction -- Editors’ Introduction -- Invited Papers -- Invention and Artificial Intelligence -- The Arrowsmith Project: 2005 Status Report -- The Robot Scientist Project -- Algorithms and Software for Collaborative Discovery from Autonomous, Semantically Heterogeneous, Distributed Information Sources -- Training Support Vector Machines via SMO-Type Decomposition Methods -- Kernel-Based Learning -- Measuring Statistical Dependence with Hilbert-Schmidt Norms -- An Analysis of the Anti-learning Phenomenon for the Class Symmetric Polyhedron -- Learning Causal Structures Based on Markov Equivalence Class -- Stochastic Complexity for Mixture of Exponential Families in Variational Bayes -- ACME: An Associative Classifier Based on Maximum Entropy Principle -- Constructing Multiclass Learners from Binary Learners: A Simple Black-Box Analysis of the Generalization Errors -- On Computability of Pattern Recognition Problems -- PAC-Learnability of Probabilistic Deterministic Finite State Automata in Terms of Variation Distance -- Learnability of Probabilistic Automata via Oracles -- Learning Attribute-Efficiently with Corrupt Oracles -- Learning DNF by Statistical and Proper Distance Queries Under the Uniform Distribution -- Learning of Elementary Formal Systems with Two Clauses Using Queries -- Gold-Style and Query Learning Under Various Constraints on the Target Class -- Non U-Shaped Vacillatory and Team Learning -- Learning Multiple Languages in Groups -- Inferring Unions of the Pattern Languages by the Most Fitting Covers -- Identification in the Limit of Substitutable Context-Free Languages -- Algorithms for Learning Regular Expressions -- A Class of Prolog Programs with Non-linear Outputs Inferable from Positive Data -- Absolute Versus Probabilistic Classification in a Logical Setting -- Online Allocation with Risk Information -- Defensive Universal Learning with Experts -- On Following the Perturbed Leader in the Bandit Setting -- Mixture of Vector Experts -- On-line Learning with Delayed Label Feedback -- Monotone Conditional Complexity Bounds on Future Prediction Errors -- Non-asymptotic Calibration and Resolution -- Defensive Prediction with Expert Advice -- Defensive Forecasting for Linear Protocols -- Teaching Learners with Restricted Mind Changes.

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Ketersediaan

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Informasi Detail

Judul Seri

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No. Panggil

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Penerbit

Berlin, Heidelberg : Springer., 2005

Deskripsi Fisik

XII, 491 p.online resource.

Bahasa

English

ISBN/ISSN

9783540316961

Klasifikasi

006.3

Tipe Isi

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Tipe Media

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Tipe Pembawa

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Edisi

1st ed.

Subjek

COMPUTERS.
Artificial intelligence.
Computation by Abstract Devices.
Algorithms.
Algorithm Analysis and Problem Complexity.
Mathematical logic.
Mathematical Logic and Formal Languages.
Natural language processing (Computer science).
Natural Language Processing (NLP).

Info Detail Spesifik

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Pernyataan Tanggungjawab

Sanjay Jain, Hans Ulrich Simon, Etsuji Tomita.

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