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001434701 001__ 1434701
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001434701 019__ $$a1240586204$$a1244118517$$a1249945260
001434701 020__ $$a9783030676582$$q(electronic bk.)
001434701 020__ $$a3030676587$$q(electronic bk.)
001434701 020__ $$z9783030676575
001434701 0247_ $$a10.1007/978-3-030-67658-2$$2doi
001434701 035__ $$aSP(OCoLC)1241066776
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001434701 049__ $$aISEA
001434701 050_4 $$aQ325.5
001434701 08204 $$a006.3/1$$223
001434701 1112_ $$aECML PKDD (Conference)$$d(2020 :$$cOnline)
001434701 24510 $$aMachine learning and knowledge discovery in databases :$$bEuropean conference, ECML PKDD 2020, Ghent, Belgium, September 14-18, 2020 : proceedings.$$nPart I /$$cFrank Hutter, Kristian Kersting, Jefrey Lijffijt, Isabel Valera (ed.).
001434701 24630 $$aECML PKDD 2020
001434701 264_1 $$aCham :$$bSpringer,$$c[2021]
001434701 300__ $$a1 online resource (l, 764 pages) :$$billustrations (chiefly color)
001434701 336__ $$atext$$btxt$$2rdacontent
001434701 337__ $$acomputer$$bc$$2rdamedia
001434701 338__ $$aonline resource$$bcr$$2rdacarrier
001434701 347__ $$atext file
001434701 347__ $$bPDF
001434701 4901_ $$aLecture notes in computer science. Lecture notes in artificial intelligence ;$$v12457
001434701 500__ $$aInternational conference proceedings.
001434701 500__ $$aIncludes author index.
001434701 5050_ $$aPattern Mining -- clustering -- privacy and fairness -- (social) network analysis and computational social science -- dimensionality reduction and autoencoders -- domain adaptation -- sketching, sampling, and binary projections -- graphical models and causality -- (spatio- ) temporal data and recurrent neural networks -- collaborative filtering and matrix completion.
001434701 506__ $$aAccess limited to authorized users.
001434701 520__ $$aThe 5-volume proceedings, LNAI 12457 until 12461 constitutes the refereed proceedings of the European Conference on Machine Learning and Knowledge Discovery in Databases, ECML PKDD 2020, which was held during September 14-18, 2020. The conference was planned to take place in Ghent, Belgium, but had to change to an online format due to the COVID-19 pandemic. The 232 full papers and 10 demo papers presented in this volume were carefully reviewed and selected for inclusion in the proceedings. The volumes are organized in topical sections as follows: Part I: Pattern Mining; clustering; privacy and fairness; (social) network analysis and computational social science; dimensionality reduction and autoencoders; domain adaptation; sketching, sampling, and binary projections; graphical models and causality; (spatio- ) temporal data and recurrent neural networks; collaborative filtering and matrix completion. Part II: deep learning optimization and theory; active learning; adversarial learning; federated learning; Kernel methods and online learning; partial label learning; reinforcement learning; transfer and multi-task learning; Bayesian optimization and few-shot learning. Part III: Combinatorial optimization; large-scale optimization and differential privacy; boosting and ensemble methods; Bayesian methods; architecture of neural networks; graph neural networks; Gaussian processes; computer vision and image processing; natural language processing; bioinformatics. Part IV: applied data science: recommendation; applied data science: anomaly detection; applied data science: Web mining; applied data science: transportation; applied data science: activity recognition; applied data science: hardware and manufacturing; applied data science: spatiotemporal data. Part V: applied data science: social good; applied data science: healthcare; applied data science: e-commerce and finance; applied data science: computational social science; applied data science: sports; demo track.
001434701 588__ $$aOnline resource; title from PDF title page (SpringerLink, viewed March 23, 2021).
001434701 650_0 $$aMachine learning$$vCongresses.
001434701 650_0 $$aData mining$$vCongresses.
001434701 650_0 $$aData structures (Computer science)
001434701 650_0 $$aApplication software.
001434701 650_0 $$aOptical data processing.
001434701 650_6 $$aApprentissage automatique$$vCongrès.
001434701 650_6 $$aExploration de données (Informatique)$$vCongrès.
001434701 650_6 $$aStructures de données (Informatique)
001434701 650_6 $$aLogiciels d'application.
001434701 650_6 $$aTraitement optique de l'information.
001434701 655_7 $$aConference papers and proceedings.$$2fast$$0(OCoLC)fst01423772
001434701 655_7 $$aConference papers and proceedings.$$2lcgft
001434701 655_7 $$aActes de congrès.$$2rvmgf
001434701 655_0 $$aElectronic books.
001434701 7001_ $$aHutter, Frank,$$eeditor.
001434701 7001_ $$aKersting, Kristian,$$eeditor.
001434701 7001_ $$aLijffijt, Jefrey,$$eeditor.
001434701 7001_ $$aValera, Isabel,$$eeditor.
001434701 77608 $$iPrint version: $$z9783030676575
001434701 77608 $$iPrint version: $$z9783030676599
001434701 830_0 $$aLecture notes in computer science.$$pLecture notes in artificial intelligence.
001434701 830_0 $$aLecture notes in computer science ;$$v12457.
001434701 852__ $$bebk
001434701 85640 $$3Springer Nature$$uhttps://univsouthin.idm.oclc.org/login?url=https://link.springer.com/10.1007/978-3-030-67658-2$$zOnline Access$$91397441.1
001434701 909CO $$ooai:library.usi.edu:1434701$$pGLOBAL_SET
001434701 980__ $$aBIB
001434701 980__ $$aEBOOK
001434701 982__ $$aEbook
001434701 983__ $$aOnline
001434701 994__ $$a92$$bISE