Inductive Logic Programming: 29th International Conference, ILP 2019, Plovdiv, Bulgaria, September 3–5, 2019, Proceedings: Lecture Notes in Computer Science, cartea 11770
Editat de Dimitar Kazakov, Can Ertenen Limba Engleză Paperback – 3 iun 2020
The 11 papers presented were carefully reviewed and selected from numerous submissions. Inductive Logic Programming (ILP) is a subfield of machine learning, which originally relied on logic programming as a uniform representation language for expressing examples, background knowledge and hypotheses. Due to its strong representation formalism, based on first-order logic, ILP provides an excellent means for multi-relational learning and data mining, and more generally for learning from structured data.
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Specificații
ISBN-13: 9783030492090
ISBN-10: 3030492095
Pagini: 200
Ilustrații: IX, 145 p. 125 illus., 19 illus. in color.
Dimensiuni: 155 x 235 mm
Greutate: 0.23 kg
Ediția:1st ed. 2020
Editura: Springer International Publishing
Colecția Springer
Seriile Lecture Notes in Computer Science, Lecture Notes in Artificial Intelligence
Locul publicării:Cham, Switzerland
ISBN-10: 3030492095
Pagini: 200
Ilustrații: IX, 145 p. 125 illus., 19 illus. in color.
Dimensiuni: 155 x 235 mm
Greutate: 0.23 kg
Ediția:1st ed. 2020
Editura: Springer International Publishing
Colecția Springer
Seriile Lecture Notes in Computer Science, Lecture Notes in Artificial Intelligence
Locul publicării:Cham, Switzerland
Cuprins
CONNER: A Concurrent ILP Learner in Description Logic.- Towards Meta-interpretive Learning of Programming Language Semantics.- Towards an ILP Application in Machine Ethics.- On the Relation Between Loss Functions and T-Norms.- Rapid Restart Hill Climbing for Learning Description Logic Concepts.- Neural Networks for Relational Data.- Learning Logic Programs from Noisy State Transition Data.- A New Algorithm for Computing Least Generalization of a Set of Atoms.- LazyBum: Decision Tree Learning Using Lazy Propositionalization.- Weight Your Words: the Effect of Different Weighting Schemes on Wordification Performance.- Learning Probabilistic Logic Programs over Continuous Data.