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_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. |
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300 |
_aXVIII, 175 p. 40 illus., 35 illus. in color. _bonline resource. |
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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. _93407 |
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650 | 0 |
_aComputer engineering. _910164 |
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650 | 0 |
_aComputer networks . _931572 |
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650 | 0 |
_aCompilers (Computer programs). _93350 |
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650 | 0 |
_aComputer science. _99832 |
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650 | 0 |
_aMachine theory. _9174715 |
|
650 | 1 | 4 |
_aArtificial Intelligence. _93407 |
650 | 2 | 4 |
_aComputer Engineering and Networks. _9174716 |
650 | 2 | 4 |
_aCompilers and Interpreters. _931853 |
650 | 2 | 4 |
_aComputer Science Logic and Foundations of Programming. _942203 |
650 | 2 | 4 |
_aFormal Languages and Automata Theory. _9174717 |
700 | 1 |
_aBellodi, Elena. _eeditor. _4edt _4http://id.loc.gov/vocabulary/relators/edt _9174718 |
|
700 | 1 |
_aLisi, Francesca Alessandra. _eeditor. _4edt _4http://id.loc.gov/vocabulary/relators/edt _9174719 |
|
700 | 1 |
_aZese, Riccardo. _eeditor. _4edt _4http://id.loc.gov/vocabulary/relators/edt _9174720 |
|
710 | 2 |
_aSpringerLink (Online service) _9174721 |
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773 | 0 | _tSpringer Nature eBook | |
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_iPrinted edition: _z9783031492983 |
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_iPrinted edition: _z9783031493003 |
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_aLecture Notes in Artificial Intelligence, _x2945-9141 ; _v14363 _9174722 |
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