01664nam0 22003733i 450 SBL014579820231121125816.0IT643948 20061213d1964 ||||0itac50 baitaitz01i xxxe z01n˜L'œopposizione mafiosa (1870-1882)baroni e mafia contro lo Stato liberaleGiuseppe Carlo Marinocon prefazione di Luigi LottiPalermoFlaccoviostampa 1964264 p., [4] c. di tav.ill.24 cmCollana di saggi e monografie. N. S13001CFI00275132001 Collana di saggi e monografie. N. S13˜L'œopposizione mafiosa (milleottocentosettanta-milleottocentottantadue) .SBL0145799SiciliaPolitica1860-1880FIRCFIC007710IMafiaStoria1870-1882FIRSBLC038586I364.106045821Marino, Giuseppe CarloCFIV0168000708270Lotti, Luigi <1931-2016>CFIV045683ITIT-0120061213IT-RM0289 IT-RM0460 IT-FR0017 Biblioteca Statale A. BaldiniRM0289 NBiblioteca Dell' Archivio Centrale Dello StatoRM0460 Biblioteca umanistica Giorgio ApreaFR0017 NSBL0145798Biblioteca umanistica Giorgio Aprea 52DES 364 Mar.Opp. 52SBA0000190615 VMB RS A 2015080320150803 04 27 52Opposizione mafiosa (1870-18821025624UNICAS04915nam 22007575 450 991055274920332120251225212330.03-030-97454-510.1007/978-3-030-97454-1(MiAaPQ)EBC6897066(Au-PeEL)EBL6897066(CKB)21383023100041(PPN)260825565(BIP)83380780(BIP)83139329(DE-He213)978-3-030-97454-1(EXLCZ)992138302310004120220223d2022 u| 0engurcnu||||||||txtrdacontentcrdamediacrrdacarrierInductive Logic Programming 30th International Conference, ILP 2021, Virtual Event, October 25–27, 2021, Proceedings /edited by Nikos Katzouris, Alexander Artikis1st ed. 2022.Cham :Springer International Publishing :Imprint: Springer,2022.1 online resource (293 pages)Lecture Notes in Artificial Intelligence,2945-9141 ;13191Includes index.Print version: Katzouris, Nikos Inductive Logic Programming Cham : Springer International Publishing AG,c2022 9783030974534 Embedding Models for Knowledge Graphs Induced by Clusters of Relations and Background Knowledge -- Fanizzi Automatic Conjecturing of P-Recursions Using Lifted Inference -- Machine learning of microbial interactions using Abductive ILP and Hypothesis Frequency/Compression Estimation -- Answer-Set Programs for Reasoning about Counterfactual Interventions and Responsibility Scores for Classification -- Reyes Synthetic Datasets and Evaluation Tools for Inductive Neural Reasoning -- Using Domain-Knowledge to Assist Lead Discovery in Early-Stage Drug Design -- Non-Parametric Learning of Embeddings for Relational Data using Gaifman Locality Theorem -- Ontology Graph Embeddings and ILP for Financial Forecasting -- Transfer learning for boosted relational dependency networks through genetic algorithm -- Online Learning of Logic Based Neural Network Structures -- Programmatic policy extraction by iterative local search -- Mapping across relational domains for transfer learning with word embeddings-based similarity -- A First Step Towards Even More Sparse Encodings of Probability Distributions -- Feature Learning by Least Generalization -- Learning Logic Programs Using Neural Networks by Exploiting Symbolic Invariance -- Learning and revising dynamic temporal theories in the full Discrete Event Calculus -- Human-like rule learning from images using one-shot hypothesis derivation -- Generative Clausal Networks: Relational Decision Trees as Probabilistic Circuits -- A Simulated Annealing Meta-heuristic for Concept Learning in Description Logics. .This book constitutes the refereed conference proceedings of the 30th International Conference on Inductive Logic Programming, ILP 2021, held in October 2021. Due to COVID-19 pandemic the conference was held virtually. The 16 papers and 3 short papers presented were carefully reviewed and selected from 19 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.Lecture Notes in Artificial Intelligence,2945-9141 ;13191Artificial intelligenceComputer engineeringComputer networksCompilers (Computer programs)Computer scienceMachine theoryArtificial IntelligenceComputer Engineering and NetworksCompilers and InterpretersComputer Science Logic and Foundations of ProgrammingFormal Languages and Automata TheoryArtificial intelligence.Computer engineering.Computer networks.Compilers (Computer programs)Computer science.Machine theory.Artificial Intelligence.Computer Engineering and Networks.Compilers and Interpreters.Computer Science Logic and Foundations of Programming.Formal Languages and Automata Theory.005.115005.115Katzouris NikosArtikis AlexanderMiAaPQMiAaPQMiAaPQBOOK9910552749203321Inductive Logic Programming2804417UNINA