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001434606 019__ $$a1249943344
001434606 020__ $$a9783030676612$$q(electronic bk.)
001434606 020__ $$a3030676617$$q(electronic bk.)
001434606 020__ $$z9783030676605
001434606 0247_ $$a10.1007/978-3-030-67661-2$$2doi
001434606 035__ $$aSP(OCoLC)1241065523
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001434606 049__ $$aISEA
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001434606 08204 $$a006.3/1$$223
001434606 1112_ $$aECML PKDD (Conference)$$d(2020 :$$cOnline)
001434606 24510 $$aMachine learning and knowledge discovery in databases :$$bEuropean conference, ECML PKDD 2020, Ghent, Belgium, September 14-18, 2020 : proceedings.$$nPart II /$$cFrank Hutter, Kristian Kersting, Jefrey Lijffijt, Isabel Valera (eds.).
001434606 24630 $$aECML PKDD 2020
001434606 264_1 $$aCham :$$bSpringer,$$c[2021]
001434606 300__ $$a1 online resource (xliii, 742 pages) :$$billustrations (chiefly color)
001434606 336__ $$atext$$btxt$$2rdacontent
001434606 337__ $$acomputer$$bc$$2rdamedia
001434606 338__ $$aonline resource$$bcr$$2rdacarrier
001434606 4901_ $$aLecture notes in computer science. Lecture notes in artificial intelligence ;$$v12458
001434606 500__ $$aInternational conference proceedings.
001434606 500__ $$aIncludes author index.
001434606 5050_ $$aDeep learning optimization and theory -- active learning -- adversarial learning; federated learning -- Kernel methods and online learning -- partial label learning -- reinforcement learning -- transfer and multi-task learning -- Bayesian optimization and few-shot learning.
001434606 506__ $$aAccess limited to authorized users.
001434606 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.
001434606 588__ $$aOnline resource; title from PDF title page (SpringerLink, viewed March 23, 2021).
001434606 650_0 $$aMachine learning$$vCongresses.
001434606 650_0 $$aData mining$$vCongresses.
001434606 650_0 $$aData mining.
001434606 650_0 $$aMachine learning.
001434606 650_0 $$aEducation$$xData processing.
001434606 650_0 $$aComputer science$$xMathematics.
001434606 650_0 $$aOptical data processing.
001434606 650_6 $$aApprentissage automatique$$vCongrès.
001434606 650_6 $$aExploration de données (Informatique)$$vCongrès.
001434606 650_6 $$aExploration de données (Informatique)
001434606 650_6 $$aApprentissage automatique.
001434606 650_6 $$aÉducation$$xInformatique.
001434606 650_6 $$aInformatique$$xMathématiques.
001434606 650_6 $$aTraitement optique de l'information.
001434606 655_7 $$aConference papers and proceedings.$$2fast$$0(OCoLC)fst01423772
001434606 655_7 $$aConference papers and proceedings.$$2lcgft
001434606 655_7 $$aActes de congrès.$$2rvmgf
001434606 655_0 $$aElectronic books.
001434606 7001_ $$aHutter, Frank,$$eeditor.
001434606 7001_ $$aKersting, Kristian,$$eeditor.
001434606 7001_ $$aLijffijt, Jefrey,$$eeditor.
001434606 7001_ $$aValera, Isabel,$$eeditor.
001434606 77608 $$iPrint version: $$z9783030676605
001434606 77608 $$iPrint version: $$z9783030676629
001434606 830_0 $$aLecture notes in computer science.$$pLecture notes in artificial intelligence.
001434606 830_0 $$aLecture notes in computer science ;$$v12458.
001434606 852__ $$bebk
001434606 85640 $$3Springer Nature$$uhttps://univsouthin.idm.oclc.org/login?url=https://link.springer.com/10.1007/978-3-030-67661-2$$zOnline Access$$91397441.1
001434606 909CO $$ooai:library.usi.edu:1434606$$pGLOBAL_SET
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