LEADER 01061nam0 22002651i 450 001 UON00306245 005 20231205104033.586 100 $a20080110d1954 |0itac50 ba 101 $aita 102 $aIT 105 $a|||| 1|||| 200 1 $aManoscritto nella battaglia$enuove poesie$fCorrado Govoni$gcon un saggio di Giuseppe Ravegnani 210 $aMilano$cMondadori$d1954 215 $aXXXV, 280 p.$d20 cm. 410 1$1001UON00029575$12001 $aˆLo ‰Specchio$ei poeti del nostro tempo$1210 $aMilano$cA. Mondadori. 620 $aIT$dMilano$3UONL000005 700 1$aGOVONI$bCorrado$3UONV174666$0176086 702 1$aRAVEGNANI$bGiuseppe$3UONV122819 712 $aMondadori$3UONV245964$4650 801 $aIT$bSOL$c20240220$gRICA 899 $aSIBA - SISTEMA BIBLIOTECARIO DI ATENEO$2UONSI 912 $aUON00306245 950 $aSIBA - SISTEMA BIBLIOTECARIO DI ATENEO$dSI ITA VI 0208 $eSI MR 54108 5 0208 996 $aManoscritto nella battaglia$91378273 997 $aUNIOR LEADER 04005nam 22007455 450 001 9910410058603321 005 20251225181927.0 010 $a3-030-49210-9 024 7 $a10.1007/978-3-030-49210-6 035 $a(CKB)5280000000218578 035 $a(MiAaPQ)EBC6297263 035 $a(DE-He213)978-3-030-49210-6 035 $a(PPN)248595083 035 $a(MiAaPQ)EBC6221052 035 $a(EXLCZ)995280000000218578 100 $a20200602d2020 u| 0 101 0 $aeng 135 $aurcnu|||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aInductive Logic Programming $e29th International Conference, ILP 2019, Plovdiv, Bulgaria, September 3?5, 2019, Proceedings /$fedited by Dimitar Kazakov, Can Erten 205 $a1st ed. 2020. 210 1$aCham :$cSpringer International Publishing :$cImprint: Springer,$d2020. 215 $a1 online resource (154 pages) 225 1 $aLecture Notes in Artificial Intelligence,$x2945-9141 ;$v11770 311 08$a3-030-49209-5 327 $aCONNER: A Concurrent ILP Learner in Description Logic -- Towards Meta-interpretive Learning of Programming Language Semantics -- Towards an ILP Application in Machine Ethics -- On the Relation Between Loss Functions and T-Norms -- Rapid Restart Hill Climbing for Learning Description Logic Concepts -- Neural Networks for Relational Data -- Learning Logic Programs from Noisy State Transition Data -- A New Algorithm for Computing Least Generalization of a Set of Atoms -- LazyBum: Decision Tree Learning Using Lazy Propositionalization -- Weight Your Words: the Effect of Different Weighting Schemes on Wordification Performance -- Learning Probabilistic Logic Programs over Continuous Data. 330 $aThis book constitutes the refereed conference proceedings of the 29th International Conference on Inductive Logic Programming, ILP 2019, held in Plovdiv, Bulgaria, in September 2019. The 11 papers presented were carefully reviewed and selected from numerous submissions. Inductive Logic Programming (ILP) is a subfield of machine learning, which originally relied on logic programming as a uniform representation language for expressing examples, background knowledge and hypotheses. Due to its strong representation formalism, based on first-order logic, ILP provides an excellent means for multi-relational learning and data mining, and more generally for learning from structured data. 410 0$aLecture Notes in Artificial Intelligence,$x2945-9141 ;$v11770 606 $aArtificial intelligence 606 $aMachine theory 606 $aComputer science 606 $aCompilers (Computer programs) 606 $aApplication software 606 $aComputer networks 606 $aArtificial Intelligence 606 $aFormal Languages and Automata Theory 606 $aComputer Science Logic and Foundations of Programming 606 $aCompilers and Interpreters 606 $aComputer and Information Systems Applications 606 $aComputer Communication Networks 615 0$aArtificial intelligence. 615 0$aMachine theory. 615 0$aComputer science. 615 0$aCompilers (Computer programs). 615 0$aApplication software. 615 0$aComputer networks. 615 14$aArtificial Intelligence. 615 24$aFormal Languages and Automata Theory. 615 24$aComputer Science Logic and Foundations of Programming. 615 24$aCompilers and Interpreters. 615 24$aComputer and Information Systems Applications. 615 24$aComputer Communication Networks. 676 $a005.115 676 $a005.115 702 $aKazakov$b Dimitar$4edt$4http://id.loc.gov/vocabulary/relators/edt 702 $aErten$b Can$4edt$4http://id.loc.gov/vocabulary/relators/edt 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910410058603321 996 $aInductive Logic Programming$92804417 997 $aUNINA