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Inductive Logic Programming = 27th International Conference, ILP 2017, Orléans, France, September 4-6, 2017, Revised Selected Papers /

紀錄類型:	書目-語言資料,印刷品 : Monograph/item
正題名/作者:	Inductive Logic Programming/ edited by Nicolas Lachiche, Christel Vrain.
其他題名:	27th International Conference, ILP 2017, Orléans, France, September 4-6, 2017, Revised Selected Papers /
其他作者:	Lachiche, Nicolas.
面頁冊數:	X, 185 p. 101 illus., 7 illus. in color.online resource. :
Contained By:	Springer Nature eBook
標題:	Mathematical logic. -
電子資源:	https://doi.org/10.1007/978-3-319-78090-0
ISBN:	9783319780900

Inductive Logic Programming = 27th International Conference, ILP 2017, Orléans, France, September 4-6, 2017, Revised Selected Papers /
Inductive Logic Programming27th International Conference, ILP 2017, Orléans, France, September 4-6, 2017, Revised Selected Papers /[electronic resource] :edited by Nicolas Lachiche, Christel Vrain. - 1st ed. 2018. - X, 185 p. 101 illus., 7 illus. in color.online resource. - Lecture Notes in Artificial Intelligence ;10759. - Lecture Notes in Artificial Intelligence ;9285.

Relational Affordance Learning for Task-dependent Robot Grasping -- Positive and Unlabeled Relational Classification Through Label Frequency Estimation -- On Applying Probabilistic Logic Programming to Breast Cancer Data -- Logical Vision: One-Shot Meta-Interpretive Learning from Real Images -- Demystifying Relational Latent Representations -- Parallel Online Learning of Event Definitions -- Relational Restricted Boltzmann Machines: A Probabilistic Logic Learning Approach -- Parallel Inductive Logic Programming System for Super-linear Speedup -- Inductive Learning from State Transitions over Continuous Domains -- Stacked Structure Learning for Lifted Relational Neural Networks -- Pruning Hypothesis Spaces Using Learned Domain Theories -- An Investigation into the Role of Domain-knowledge on the Use of Embeddings.

This book constitutes the thoroughly refereed post-conference proceedings of the 27th International Conference on Inductive Logic Programming, ILP 2017, held in Orléans, France, in September 2017. The 12 full 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.

ISBN: 9783319780900

Standard No.: 10.1007/978-3-319-78090-0doiSubjects--Topical Terms:

810627
Mathematical logic.

LC Class. No.: QA8.9-10.3

Dewey Class. No.: 005.131

Inductive Logic Programming = 27th International Conference, ILP 2017, Orléans, France, September 4-6, 2017, Revised Selected Papers /
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