001480955 000__ 04629cam\\22006857i\4500
001480955 001__ 1480955
001480955 003__ OCoLC
001480955 005__ 20231031003316.0
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001480955 007__ cr\un\nnnunnun
001480955 008__ 230920s2023\\\\sz\a\\\\o\\\\\101\0\eng\d
001480955 020__ $$a9783031434303$$q(electronic bk.)
001480955 020__ $$a3031434307$$q(electronic bk.)
001480955 020__ $$z9783031434297
001480955 0247_ $$a10.1007/978-3-031-43430-3$$2doi
001480955 035__ $$aSP(OCoLC)1398308939
001480955 040__ $$aGW5XE$$beng$$erda$$epn$$cGW5XE$$dOCLCO$$dWSU
001480955 049__ $$aISEA
001480955 050_4 $$aQ325.5
001480955 08204 $$a006.3/1$$223/eng/20230920
001480955 1112_ $$aECML PKDD (Conference)$$d(2023 :$$cTurin, Italy)
001480955 24510 $$aMachine learning and knowledge discovery in databases :$$bApplied data science and demo track : European Conference, ECML PKDD 2023, Turin, Italy, September 18-22, 2023, Proceedings.$$nPart VII /$$cGianmarco De Francisci Morales, Claudia Perlich, Natali Ruchansky, Nicolas Kourtellis, Elena Baralis, Francesco Bonchi, editors.
001480955 2463_ $$aECML PKDD 2023
001480955 264_1 $$aCham :$$bSpringer,$$c2023.
001480955 300__ $$a1 online resource (liv, 381 pages) :$$billustrations (some color).
001480955 336__ $$atext$$btxt$$2rdacontent
001480955 337__ $$acomputer$$bc$$2rdamedia
001480955 338__ $$aonline resource$$bcr$$2rdacarrier
001480955 4901_ $$aLecture notes in artificial intelligence
001480955 4901_ $$aLecture notes in computer science ;$$v14175
001480955 4901_ $$aLNCS sublibrary, SL 7, Artificial intelligence
001480955 500__ $$aIncludes author index.
001480955 5050_ $$aSustainability, Climate, and Environment -- Transportation & Urban Planning -- Demo.
001480955 506__ $$aAccess limited to authorized users.
001480955 520__ $$aThe multi-volume set LNAI 14169 until 14175 constitutes the refereed proceedings of the European Conference on Machine Learning and Knowledge Discovery in Databases, ECML PKDD 2023, which took place in Turin, Italy, in September 2023. The 196 papers were selected from the 829 submissions for the Research Track, and 58 papers were selected from the 239 submissions for the Applied Data Science Track. The volumes are organized in topical sections as follows: Part I: Active Learning; Adversarial Machine Learning; Anomaly Detection; Applications; Bayesian Methods; Causality; Clustering. Part II: Computer Vision; Deep Learning; Fairness; Federated Learning; Few-shot learning; Generative Models; Graph Contrastive Learning. Part III: Graph Neural Networks; Graphs; Interpretability; Knowledge Graphs; Large-scale Learning. Part IV: Natural Language Processing; Neuro/Symbolic Learning; Optimization; Recommender Systems; Reinforcement Learning; Representation Learning. Part V: Robustness; Time Series; Transfer and Multitask Learning. Part VI: Applied Machine Learning; Computational Social Sciences; Finance; Hardware and Systems; Healthcare & Bioinformatics; Human-Computer Interaction; Recommendation and Information Retrieval. Part VII: Sustainability, Climate, and Environment.- Transportation & Urban Planning.- Demo.
001480955 588__ $$aOnline resource; title from PDF title page (SpringerLink, viewed September 20, 2023).
001480955 650_6 $$aApprentissage automatique$$vCongrès.
001480955 650_6 $$aExploration de données (Informatique)$$vCongrès.
001480955 650_0 $$aMachine learning$$vCongresses.$$vCongresses$$0(DLC)sh2008107143
001480955 650_0 $$aData mining$$vCongresses.$$vCongresses$$0(DLC)sh2008102035
001480955 650_0 $$aDatabases$$vCongresses.$$0(DLC)sh2016002790
001480955 655_7 $$aConference papers and proceedings.$$2lcgft
001480955 655_0 $$aElectronic books.
001480955 7001_ $$aDe Francisci Morales, Gianmarco,$$eeditor.$$0(orcid)0000-0002-2415-494X$$1https://orcid.org/0000-0002-2415-494X
001480955 7001_ $$aPerlich, Claudia,$$eeditor.
001480955 7001_ $$aRuchansky, Natali,$$eeditor.$$0(orcid)0000-0002-0367-4807$$1https://orcid.org/0000-0002-0367-4807
001480955 7001_ $$aKourtellis, Nicolas,$$eeditor.$$0(orcid)0000-0002-5674-1698$$1https://orcid.org/0000-0002-5674-1698
001480955 7001_ $$aBaralis, Elena,$$eeditor.$$0(orcid)0000-0001-9231-467X$$1https://orcid.org/0000-0001-9231-467X
001480955 7001_ $$aBonchi, Francesco,$$eeditor.$$1https://orcid.org/0000-0001-9464-8315
001480955 830_0 $$aLecture notes in computer science.$$pLecture notes in artificial intelligence.
001480955 830_0 $$aLecture notes in computer science ;$$v14175.
001480955 830_0 $$aLNCS sublibrary.$$nSL 7,$$pArtificial intelligence.
001480955 852__ $$bebk
001480955 85640 $$3Springer Nature$$uhttps://univsouthin.idm.oclc.org/login?url=https://link.springer.com/10.1007/978-3-031-43430-3$$zOnline Access$$91397441.1
001480955 909CO $$ooai:library.usi.edu:1480955$$pGLOBAL_SET
001480955 980__ $$aBIB
001480955 980__ $$aEBOOK
001480955 982__ $$aEbook
001480955 983__ $$aOnline
001480955 994__ $$a92$$bISE