An Efficient Approximation to Lookahead in Relational Learners
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Lookahead increases the complexity of learning.
“To avoid this issue, these systems rely on lookahead (Struyf et al., 2006) which increases the complexity of learning.”
From Inductive Logic Programming At 30: A New Introduction (2022) · cites this paper as Struyf et al., 2006
These systems rely on lookahead to avoid the issue of getting stuck with suboptimal solutions.
“To avoid this issue, these systems rely on lookahead (Struyf et al., 2006) which increases the complexity of learning.”
From Inductive Logic Programming At 30: A New Introduction (2022) · cites this paper as Struyf et al., 2006
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Cites
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Inductive Logic Programming At 30: A New Introduction
Cropper, A., & Dumančić, S. (2022) · Journal of Artificial Intelligence Research · doi:10.1613/jair.1.13507 · Cited by 83 · see citing works
“To avoid this issue, these systems rely on lookahead (Struyf et al., 2006) which increases the complexity of learning.”
BackgroundLifted discriminative learning of probabilistic logic programs
Fadja, A. N., & Riguzzi, F. (2018) · Machine Learning · doi:10.1007/s10994-018-5750-0 · Cited by 12 · see citing works
Lippi, M., Jaeger, M., Frasconi, P., & Passerini, A. (2010) · Machine Learning · doi:10.1007/s10994-010-5194-7 · Cited by 9 · see citing works
Regularization in Probabilistic Inductive Logic Programming
Gentili, E., Bizzarri, A., Azzolini, D., Zese, R., & Riguzzi, F. (2023) · Lecture notes in computer science · doi:10.1007/978-3-031-49299-0_2 · Cited by 2 · see citing works
Statistical learning for relational and structured data
Lippi, M. (2009) · Florence Research (University of Florence)
- Authors
- Struyf, J., Davis, J., & Page, D.
- Affiliations
- KU Leuven (BE)
- University of Wisconsin–Madison (US)
- Venue
- Lecture Notes in Computer Science
- Publisher
- Springer Berlin Heidelberg
- Published
- 2006
- Pages
- 775-782
- ISSN
- 0302-9743 (ISSN-L)
- 1611-3349
- OpenAlex
- W1550337014
- Cited by
- 5
- References
- 12
- Citations by year
- 2023: 1 · 2022: 1 · 2018: 1
- FWCI
- 0.26
- Type
- conference paper
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- Lecture notes in computer science (publishedVersion)
- Lirias (submittedVersion, other-oa)
- Funders
- National Science Foundation (0534908)
- Fonds Wetenschappelijk Onderzoek
- Vlaamse regering
- Topics
- Physical Sciences › Computer Science › Information Systems › Data Mining Algorithms and Applications
- Physical Sciences › Computer Science › Artificial Intelligence › Logic, Reasoning, and Knowledge
- Physical Sciences › Computer Science › Artificial Intelligence › AI-based Problem Solving and Planning
- Keywords
- lookahead, greedy search, relational learning, inductive logic programming, search heuristics, overfitting, search space exploration
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