Übersicht			Auf mobile öffnen

Lieferstatus:	Auf Bestellung (Lieferzeit unbekannt)
Veröffentlichung:	September 2005
Genre:	EDV / Informatik
	Algorithm Analysis and Problem Complexity / Algorithmen und Datenstrukturen / Algorithms / Algorithms & data structures / Artificial Intelligence / C / Computation by Abstract Devices / computer science / Computers / Formal Languages and Automata Theory / Mathematical logic / Mathematical Logic and Formal Languages / Mathematical theory of computation / Natural language & machine translation / Natural language processing (Computer science) / Natural Language Processing (NLP) / Natürliche Sprachen und maschinelle Übersetzung / Theoretische Informatik / Theory of Computation mehr...
ISBN:	9783540292425
EAN-Code:	9783540292425
Verlag:	Springer EN
Einband:	Kartoniert
Sprache:	English
Serie:	Lecture Notes in Artificial Intelligence #3734 - Lecture Notes in Computer Science
Dimensionen:	H 235 mm / B 155 mm / D
Gewicht:	1560 gr
Seiten:	491
Illustration:	XII, 491 p.
Zus. Info:	EUDR exemption - product or manufacturing materials placed on the market prior to 31.12.2025.
Bewertung:	Titel bewerten / Meinung schreiben

Inhalt:

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.