Suchergebnisse - "inductive logic programming"

Towards Probabilistic Inductive Logic Programming with Neurosymbolic Inference and Relaxation

Autoren: FIEKE HILLERSTRÖM GERTJAN BURGHOUTS DSS - Defence, Safety & Security et al.

Weitere Verfasser: FIEKE HILLERSTRÖM GERTJAN BURGHOUTS DSS - Defence, Safety & Security et al.

Quelle: Theory and Practice of Logic Programming, 24(4), pp. 628-643.

Schlagwörter: FOS: Computer and information sciences, Computer Science - Machine Learning, Artificial Intelligence (cs.AI), Sensory data, Computer Science - Artificial Intelligence, Probabilistic background knowledge, Inductive logic programming, Neurosymbolic inference, Relational patterns, Machine Learning (cs.LG)

Zugangs-URL: http://arxiv.org/abs/2408.11367
https://publications.tno.nl/publication/34643722/h3r4B1wu/TNO-2025-P10140.pdf
https://resolver.tno.nl/uuid:b366fa16-c6b6-46b1-9fb7-c67b83ea456e

Task-To-Processor Assignment for Real-Time Mixed-Critical Networked Systems Using Inductive Logic Programming

Autoren: Gualtieri, Marcus Juette, Christian Dasari, Dakshina et al.

Weitere Verfasser: Gualtieri, Marcus Juette, Christian Dasari, Dakshina et al.

Schlagwörter: Auto-Configuration, Task-to-Processor Mapping, Active Learning, ddc:004, Real-Time Distributed Systems, Inductive Logic Programming

Dateibeschreibung: application/pdf

Zugangs-URL: https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.ECRTS.2025.14

Towards Probabilistic Inductive Logic Programming with Neurosymbolic Inference and Relaxation

Autoren: Hillerström, F.H.J. Burghouts, G.J. DSS - Defence, Safety & Security et al.

Weitere Verfasser: Hillerström, F.H.J. Burghouts, G.J. DSS - Defence, Safety & Security et al.

Quelle: Theory and Practice of Logic Programming, 24(4), pp. 628-643.

Schlagwörter: Sensory data, Probabilistic background knowledge, Inductive logic programming, Neurosymbolic inference, Relational patterns

Zugangs-URL: https://publications.tno.nl/publication/34643722/h3r4B1wu/TNO-2025-P10140.pdf
https://resolver.tno.nl/uuid:b366fa16-c6b6-46b1-9fb7-c67b83ea456e

Proxy Attribute Discovery in Machine Learning Datasets via Inductive Logic Programming (Extended Version)

Autoren: Goncalves, Rafael Gouveia, Filipe Lynce, Ines et al.

Schlagwörter: Machine Learning, Proxy Attributes, Fairness, Inductive Logic Programming

A Critical Review of Inductive Logic Programming Techniques for Explainable AI

Autoren: Zheng Zhang Levent Yilmaz Bo Liu

Quelle: IEEE Transactions on Neural Networks and Learning Systems. 35:10220-10236

Zugangs-URL: https://pubmed.ncbi.nlm.nih.gov/37018093

Proxy Attribute Discovery in Machine Learning Datasets via Inductive Logic Programming

Autoren: Rafael Gonçalves Filipe Gouveia Inês Lynce et al.

Quelle: Lecture Notes in Computer Science ISBN: 9783031906527

Program Synthesis Using Inductive Logic Programming for the Abstraction and Reasoning Corpus

Autoren: Filipe Marinho Rocha Inês Dutra Vítor Santos Costa et al.

Quelle: Communications in Computer and Information Science ISBN: 9783031893650

On Bridging Prolog and Python to Enhance an Inductive Logic Programming System

Autoren: Vítor Santos Costa Miguel Areias

Quelle: Lecture Notes in Computer Science ISBN: 9783031849237

Using Incremental Inductive Logic Programming for Learning Spoofing Attacks on Maritime Automatic Identification System Data

Autoren: Aboubaker Seddiq Benterki Gabor Visky Jüri Vain et al.

Quelle: Signals and Communication Technology ISBN: 9783031872891

Multi-grain Parallel Processing of Inductive Logic Programming

Autoren: Moeko Okawara Munehiro Takimoto

Quelle: Communications in Computer and Information Science ISBN: 9783031903403

Inductive Logic Programming based Bottlenose Delphin Optimization to Fake new Detection

Autoren: Gunasekar Thangarasu Rao Alla Kesava K Nattar Kannan

Quelle: 2024 IEEE 14th Symposium on Computer Applications & Industrial Electronics (ISCAIE). :153-158

Towards Multimodal Co-Construction of Explanations for Robots: Combining Inductive Logic Programming and Large Language Models to Explain Robot Faults

Autoren: Youssef Mahmoud Youssef Teena Hassan

Quelle: Companion Proceedings of the 26th International Conference on Multimodal Interaction. :228-230

Abductive Logical Rule Induction by Bridging Inductive Logic Programming and Multimodal Large Language Models

Autoren: Peng, Yifei Liu, Yaoli Xia, Enbo et al.

Schlagwörter: Machine Learning, FOS: Computer and information sciences, Machine Learning (cs.LG)

Zugangs-URL: http://arxiv.org/abs/2509.21874

Symmetry breaking for inductive logic programming

Autoren: Cropper, Andrew Cerna, David M. Järvisalo, Matti

Schlagwörter: Machine Learning, FOS: Computer and information sciences, Artificial Intelligence (cs.AI), Artificial Intelligence, Machine Learning (cs.LG)

Zugangs-URL: http://arxiv.org/abs/2508.06263

GLIDR: Graph-Like Inductive Logic Programming with Differentiable Reasoning

Autoren: Johnson, Blair Kerce, Clayton Fekri, Faramarz

Schlagwörter: Machine Learning, FOS: Computer and information sciences, Artificial Intelligence (cs.AI), Artificial Intelligence, Logic in Computer Science, Machine Learning (cs.LG), Logic in Computer Science (cs.LO)

Zugangs-URL: http://arxiv.org/abs/2508.06716

Self-Supervised Inductive Logic Programming

Autoren: Patsantzis, Stassa

Schlagwörter: Machine Learning, FOS: Computer and information sciences, Artificial Intelligence (cs.AI), Artificial Intelligence, Machine Learning (cs.LG)

Zugangs-URL: http://arxiv.org/abs/2507.16405

Robust Hypothesis Generation: LLM-Automated Language Bias for Inductive Logic Programming

Autoren: Yang, Yang Wu, Jiemin Yue, Yutao

Schlagwörter: FOS: Computer and information sciences, Artificial Intelligence (cs.AI), Computer Science - Artificial Intelligence

Zugangs-URL: http://arxiv.org/abs/2505.21486

An Empirical Comparison of Cost Functions in Inductive Logic Programming

Autoren: Hocquette, Céline Cropper, Andrew

Schlagwörter: FOS: Computer and information sciences, Computer Science - Machine Learning, Machine Learning (cs.LG)

Zugangs-URL: http://arxiv.org/abs/2503.07554

Inductive logic programming applied for knowledge representation in computer music/ Programação lógica indutiva aplicada para representação do conhecimento em música computacional

Autoren: Gonçalves Júnior, Clenio Batista Homem, Murillo Rodrigo Petrucelli

Quelle: Brazilian Applied Science Review; Vol. 5 No. 4 (2021); 1840-1857
Brazilian Applied Science Review; v. 5 n. 4 (2021); 1840-1857
Brazilian Applied Science Review
Brazilian Journals Publicações de Periódicos e Editora Ltda
instacron:FIEP

Schlagwörter: Artificial intelligence, Knowledge representation, CIENCIAS EXATAS E DA TERRA::CIENCIA DA COMPUTACAO, Artificial Intelligence, Machine learning, Computer Music, Computer music, Machine Learning, Inductive logic programming, Knowledge Representation, Inductive Logic Programming

Dateibeschreibung: application/pdf

Zugangs-URL: https://www.brazilianjournals.com/index.php/BASR/article/viewFile/33034/pdf
https://ojs.brazilianjournals.com.br/ojs/index.php/BASR/article/view/33034

Inductive Logic Programming. 32nd International Conference on Inductive Logic Programming, ILP 2023, Bari, Italy, November 13–15, 2023, Proceedings

Autoren: Elena Bellodi Riccardo Zese Francesca Lisi

Schlagwörter: Inductive Logic Programming

Dateibeschreibung: application/pdf

Zugangs-URL: https://hdl.handle.net/11392/2559330
https://link.springer.com/book/10.1007/978-3-031-49299-0