Übersicht			Auf mobile öffnen

Lieferstatus:	Auf Bestellung (Lieferzeit unbekannt)
Veröffentlichung:	März 2008
Genre:	EDV / Informatik
	Algorithm Analysis and Problem Complexity / Algorithms / Algorithms & data structures / Artificial Intelligence / C / Computer programming / Computer programming / software engineering / computer science / Data Mining / Data Mining and Knowledge Discovery / Expert systems / knowledge-based systems / Formal Languages and Automata Theory / Mathematical logic / Mathematical Logic and Formal Languages / Mathematical theory of computation / Operating systems / Programming Techniques / Software Engineering / Software Engineering/Programming and Operating Systems / Wissensbasierte Systeme, Expertensysteme mehr...
ISBN:	9783540784685
EAN-Code:	9783540784685
Verlag:	Springer EN
Einband:	Kartoniert
Sprache:	English
Serie:	Lecture Notes in Artificial Intelligence #4894 - Lecture Notes in Computer Science
Dimensionen:	H 235 mm / B 155 mm / D
Gewicht:	504 gr
Seiten:	307
Illustration:	XI, 307 p.
Zus. Info:	EUDR exemption - product or manufacturing materials placed on the market prior to 31.12.2025.
Bewertung:	Titel bewerten / Meinung schreiben

Inhalt:

Invited Talks.- Learning with Kernels and Logical Representations.- Beyond Prediction: Directions for Probabilistic and Relational Learning.- Extended Abstracts.- Learning Probabilistic Logic Models from Probabilistic Examples (Extended Abstract).- Learning Directed Probabilistic Logical Models Using Ordering-Search.- Learning to Assign Degrees of Belief in Relational Domains.- Bias/Variance Analysis for Relational Domains.- Full Papers.- Induction of Optimal Semantic Semi-distances for Clausal Knowledge Bases.- Clustering Relational Data Based on Randomized Propositionalization.- Structural Statistical Software Testing with Active Learning in a Graph.- Learning Declarative Bias.- ILP :- Just Trie It.- Learning Relational Options for Inductive Transfer in Relational Reinforcement Learning.- Empirical Comparison of "Hard" and "Soft" Label Propagation for Relational Classification.- A Phase Transition-Based Perspective on Multiple Instance Kernels.- Combining Clauses with Various Precisions and Recalls to Produce Accurate Probabilistic Estimates.- Applying Inductive Logic Programming to Process Mining.- A Refinement Operator Based Learning Algorithm for the Description Logic.- Foundations of Refinement Operators for Description Logics.- A Relational Hierarchical Model for Decision-Theoretic Assistance.- Using Bayesian Networks to Direct Stochastic Search in Inductive Logic Programming.- Revising First-Order Logic Theories from Examples Through Stochastic Local Search.- Using ILP to Construct Features for Information Extraction from Semi-structured Text.- Mode-Directed Inverse Entailment for Full Clausal Theories.- Mining of Frequent Block Preserving Outerplanar Graph Structured Patterns.- Relational Macros for Transfer in Reinforcement Learning.- Seeing theForest Through the Trees.- Building Relational World Models for Reinforcement Learning.- An Inductive Learning System for XML Documents.