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020 _a9783031492990
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024 7 _a10.1007/978-3-031-49299-0
_2doi
050 4 _aQ334-342
050 4 _aTA347.A78
072 7 _aUYQ
_2bicssc
072 7 _aCOM004000
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245 1 0 _aInductive Logic Programming
_h[electronic resource] :
_b32nd International Conference, ILP 2023, Bari, Italy, November 13–15, 2023, Proceedings /
_cedited by Elena Bellodi, Francesca Alessandra Lisi, Riccardo Zese.
250 _a1st ed. 2023.
264 1 _aCham :
_bSpringer Nature Switzerland :
_bImprint: Springer,
_c2023.
300 _aXVIII, 175 p. 40 illus., 35 illus. in color.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
490 1 _aLecture Notes in Artificial Intelligence,
_x2945-9141 ;
_v14363
505 0 _aDeclarative Sequential Pattern Mining in ASP -- Extracting Rules from ML models in Angluin’s Style -- A Constrained Optimization Approach to Set the Parameters of Probabilistic Answer Set Programs -- Regularization in Probabilistic Inductive Logic Programming -- Towards ILP-based LTLf passive learning -- Learning Strategies of Inductive Logic Programming Using Reinforcement Learning -- Select first, transfer later: choosing proper datasets for statistical relational transfer learning -- GNN based Extraction of Minimal Unsatisfiable Subsets -- What Do Counterfactuals Say about the World? Reconstructing Probabilistic Logic Programs from Answers to “What if?” Queries -- Few-shot learning of diagnostic rules for neurodegenerative diseases using Inductive Logic Programming -- An Experimental Overview of Neural-Symbolic Systems -- Statistical relational structure learning with scaled weight parameters -- A Review of Inductive Logic Programming Applications for Robotic Systems -- Meta Interpretive Learning from Fractal images.
520 _aThis book constitutes the refereed proceedings of the 32nd International Conference on Inductive Logic Programming, ILP 2023, held in Bari, Italy, during November 13–15, 2023. The 11 full papers and 1 short paper included in this book were carefully reviewed and selected from 18 submissions. They cover all aspects of learning in logic, multi-relational data mining, statistical relational learning, graph and tree mining, learning in other (non-propositional) logic-based knowledge representation frameworks, exploring intersections to statistical learning and other probabilistic approaches.
650 0 _aArtificial intelligence.
650 0 _aComputer engineering.
650 0 _aComputer networks .
650 0 _aCompilers (Computer programs).
650 0 _aComputer science.
650 0 _aMachine theory.
650 1 4 _aArtificial Intelligence.
650 2 4 _aComputer Engineering and Networks.
650 2 4 _aCompilers and Interpreters.
650 2 4 _aComputer Science Logic and Foundations of Programming.
650 2 4 _aFormal Languages and Automata Theory.
700 1 _aBellodi, Elena.
_eeditor.
_4edt
_4http://id.loc.gov/vocabulary/relators/edt
700 1 _aLisi, Francesca Alessandra.
_eeditor.
_4edt
_4http://id.loc.gov/vocabulary/relators/edt
700 1 _aZese, Riccardo.
_eeditor.
_4edt
_4http://id.loc.gov/vocabulary/relators/edt
710 2 _aSpringerLink (Online service)
773 0 _tSpringer Nature eBook
776 0 8 _iPrinted edition:
_z9783031492983
776 0 8 _iPrinted edition:
_z9783031493003
830 0 _aLecture Notes in Artificial Intelligence,
_x2945-9141 ;
_v14363
856 4 0 _uhttps://doi.org/10.1007/978-3-031-49299-0
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