001480956 000__ 04550cam\\22006857i\4500
001480956 001__ 1480956
001480956 003__ OCoLC
001480956 005__ 20231031003316.0
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001480956 008__ 230920s2023\\\\sz\a\\\\o\\\\\101\0\eng\d
001480956 020__ $$a9783031434211$$q(electronic bk.)
001480956 020__ $$a3031434218$$q(electronic bk.)
001480956 020__ $$z9783031434204
001480956 0247_ $$a10.1007/978-3-031-43421-1$$2doi
001480956 035__ $$aSP(OCoLC)1398309594
001480956 040__ $$aGW5XE$$beng$$erda$$epn$$cGW5XE$$dOCLCO$$dWSU
001480956 049__ $$aISEA
001480956 050_4 $$aQ325.5
001480956 08204 $$a006.3/1$$223/eng/20230920
001480956 1112_ $$aECML PKDD (Conference)$$d(2023 :$$cTurin, Italy)
001480956 24510 $$aMachine learning and knowledge discovery in databases :$$bResearch track : European Conference, ECML PKDD 2023, Turin, Italy, September 18-22, 2023, Proceedings.$$nPart IV /$$cDanai Koutra, Claudia Plant, Manuel Gomez Rodriguez, Elena Baralis, Francesco Bonchi, editors.
001480956 2463_ $$aECML PKDD 2023
001480956 2463_ $$aResearch track
001480956 264_1 $$aCham :$$bSpringer,$$c2023.
001480956 300__ $$a1 online resource (lv, 747 pages) :$$billustrations (some color).
001480956 336__ $$atext$$btxt$$2rdacontent
001480956 337__ $$acomputer$$bc$$2rdamedia
001480956 338__ $$aonline resource$$bcr$$2rdacarrier
001480956 4901_ $$aLecture notes in artificial intelligence
001480956 4901_ $$aLecture notes in computer science ;$$v14172
001480956 4901_ $$aLNCS sublibrary, SL 7, Artificial intelligence
001480956 500__ $$aIncludes author index.
001480956 5050_ $$aNatural Language Processing -- Neuro/Symbolic Learning -- Optimization -- Recommender Systems -- Reinforcement Learning -- Representation Learning.
001480956 506__ $$aAccess limited to authorized users.
001480956 520__ $$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.
001480956 588__ $$aOnline resource; title from PDF title page (SpringerLink, viewed September 20, 2023).
001480956 650_6 $$aApprentissage automatique$$vCongrès.
001480956 650_6 $$aExploration de données (Informatique)$$vCongrès.
001480956 650_0 $$aMachine learning$$vCongresses.$$vCongresses$$0(DLC)sh2008107143
001480956 650_0 $$aData mining$$vCongresses.$$vCongresses$$0(DLC)sh2008102035
001480956 650_0 $$aDatabases$$vCongresses.$$0(DLC)sh2016002790
001480956 655_7 $$aConference papers and proceedings.$$2lcgft
001480956 655_0 $$aElectronic books.
001480956 7001_ $$aKoutra, Danai,$$eeditor.$$1https://orcid.org/0000-0002-3206-8179
001480956 7001_ $$aPlant, Claudia,$$eeditor.$$1https://orcid.org/0000-0001-5274-8123
001480956 7001_ $$aGomez Rodriguez, Manuel,$$eeditor.$$0(orcid)0000-0003-3930-1161$$1https://orcid.org/0000-0003-3930-1161
001480956 7001_ $$aBaralis, Elena,$$eeditor.$$0(orcid)0000-0001-9231-467X$$1https://orcid.org/0000-0001-9231-467X
001480956 7001_ $$aBonchi, Francesco,$$eeditor.$$1https://orcid.org/0000-0001-9464-8315
001480956 830_0 $$aLecture notes in computer science.$$pLecture notes in artificial intelligence.
001480956 830_0 $$aLecture notes in computer science ;$$v14172.
001480956 830_0 $$aLNCS sublibrary.$$nSL 7,$$pArtificial intelligence.
001480956 852__ $$bebk
001480956 85640 $$3Springer Nature$$uhttps://univsouthin.idm.oclc.org/login?url=https://link.springer.com/10.1007/978-3-031-43421-1$$zOnline Access$$91397441.1
001480956 909CO $$ooai:library.usi.edu:1480956$$pGLOBAL_SET
001480956 980__ $$aBIB
001480956 980__ $$aEBOOK
001480956 982__ $$aEbook
001480956 983__ $$aOnline
001480956 994__ $$a92$$bISE