Übersicht			Auf mobile öffnen

Lieferstatus:	Auf Bestellung (Lieferzeit unbekannt)
Veröffentlichung:	September 2006
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:	9783540466499
EAN-Code:	9783540466499
Verlag:	Springer EN
Einband:	Kartoniert
Sprache:	English
Serie:	Lecture Notes in Artificial Intelligence #4264 - Lecture Notes in Computer Science
Dimensionen:	H 235 mm / B 155 mm / D
Gewicht:	1270 gr
Seiten:	393
Illustration:	XIII, 393 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 Contributions.- Solving Semi-infinite Linear Programs Using Boosting-Like Methods.- e-Science and the Semantic Web: A Symbiotic Relationship.- Spectral Norm in Learning Theory: Some Selected Topics.- Data-Driven Discovery Using Probabilistic Hidden Variable Models.- Reinforcement Learning and Apprenticeship Learning for Robotic Control.- Regular Contributions.- Learning Unions of ?(1)-Dimensional Rectangles.- On Exact Learning Halfspaces with Random Consistent Hypothesis Oracle.- Active Learning in the Non-realizable Case.- How Many Query Superpositions Are Needed to Learn?.- Teaching Memoryless Randomized Learners Without Feedback.- The Complexity of Learning SUBSEQ (A).- Mind Change Complexity of Inferring Unbounded Unions of Pattern Languages from Positive Data.- Learning and Extending Sublanguages.- Iterative Learning from Positive Data and Negative Counterexamples.- Towards a Better Understanding of Incremental Learning.- On Exact Learning from Random Walk.- Risk-Sensitive Online Learning.- Leading Strategies in Competitive On-Line Prediction.- Hannan Consistency in On-Line Learning in Case of Unbounded Losses Under Partial Monitoring.- General Discounting Versus Average Reward.- The Missing Consistency Theorem for Bayesian Learning: Stochastic Model Selection.- Is There an Elegant Universal Theory of Prediction?.- Learning Linearly Separable Languages.- Smooth Boosting Using an Information-Based Criterion.- Large-Margin Thresholded Ensembles for Ordinal Regression: Theory and Practice.- Asymptotic Learnability of Reinforcement Problems with Arbitrary Dependence.- Probabilistic Generalization of Simple Grammars and Its Application to Reinforcement Learning.- Unsupervised Slow Subspace-Learning fromStationary Processes.- Learning-Related Complexity of Linear Ranking Functions.