001434654 000__ 05572cam\a2200805\i\4500 001434654 001__ 1434654 001434654 003__ OCoLC 001434654 005__ 20230309003811.0 001434654 006__ m\\\\\o\\d\\\\\\\\ 001434654 007__ cr\un\nnnunnun 001434654 008__ 210224s2021\\\\sz\a\\\\o\\\\\101\0\eng\d 001434654 019__ $$a1239962288$$a1240584421$$a1244119358$$a1249945081$$a1253403978 001434654 020__ $$a9783030676704$$q(electronic bk.) 001434654 020__ $$a3030676706$$q(electronic bk.) 001434654 020__ $$a9783030676711$$q(print) 001434654 020__ $$a3030676714 001434654 020__ $$z9783030676698 001434654 020__ $$z3030676692 001434654 0247_ $$a10.1007/978-3-030-67670-4$$2doi 001434654 035__ $$aSP(OCoLC)1241066281 001434654 040__ $$aDKU$$beng$$erda$$epn$$cDKU$$dOCLCO$$dOCLCQ$$dYDXIT$$dGW5XE$$dOCLCO$$dEBLCP$$dYDX$$dDCT$$dOCLCF$$dN$T$$dLEATE$$dVT2$$dLIP$$dOCLCO$$dOCLCQ$$dOCLCO$$dCOM$$dOCLCQ 001434654 049__ $$aISEA 001434654 050_4 $$aQ325.5 001434654 08204 $$a006.3/1$$223 001434654 1112_ $$aECML PKDD (Conference)$$d(2020 :$$cOnline) 001434654 24510 $$aMachine learning and knowledge discovery in databases :$$bapplied data science and demo track : European conference, ECML PKDD 2020, Ghent, Belgium, September 14-18, 2020 : proceedings.$$nPart V /$$cYuxiao Dong, Georgiana Ifrim, Dunja Mladenić, Craig Saunders, Sofie Van Hoecke (eds.). 001434654 24630 $$aECML PKDD 2020 001434654 264_1 $$aCham :$$bSpringer,$$c[2021] 001434654 300__ $$a1 online resource (xlii, 577 pages) :$$billustrations (chiefly color) 001434654 336__ $$atext$$btxt$$2rdacontent 001434654 337__ $$acomputer$$bc$$2rdamedia 001434654 338__ $$aonline resource$$bcr$$2rdacarrier 001434654 347__ $$atext file 001434654 347__ $$bPDF 001434654 4901_ $$aLecture notes in computer science. Lecture notes in artificial intelligence ;$$v12461 001434654 500__ $$aInternational conference proceedings. 001434654 500__ $$aIncludes author index. 001434654 5050_ $$aApplied data science: recommendation -- applied data science: anomaly detection -- applied data science: Web mining -- applied data science: transportation -- applied data science: activity recognition -- applied data science: hardware and manufacturing -- applied data science: spatiotemporal data. 001434654 506__ $$aAccess limited to authorized users. 001434654 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. 001434654 588__ $$aOnline resource; title from PDF title page (SpringerLink, viewed March 23, 2021). 001434654 650_0 $$aMachine learning$$vCongresses. 001434654 650_0 $$aData mining$$vCongresses. 001434654 650_0 $$aEducation$$xData processing. 001434654 650_0 $$aApplication software. 001434654 650_0 $$aComputer organization. 001434654 650_6 $$aApprentissage automatique$$vCongrès. 001434654 650_6 $$aExploration de données (Informatique)$$vCongrès. 001434654 650_6 $$aÉducation$$xInformatique. 001434654 650_6 $$aLogiciels d'application. 001434654 650_6 $$aOrdinateurs$$xConception et construction. 001434654 655_7 $$aConference papers and proceedings.$$2fast$$0(OCoLC)fst01423772 001434654 655_7 $$aConference papers and proceedings.$$2lcgft 001434654 655_7 $$aActes de congrès.$$2rvmgf 001434654 655_0 $$aElectronic books. 001434654 7001_ $$aDong, Yuxiao,$$eeditor. 001434654 7001_ $$aIfrim, Georgiana,$$eeditor. 001434654 7001_ $$aMladenić, Dunja,$$d1967-$$eeditor. 001434654 7001_ $$aSaunders, Craig,$$eeditor. 001434654 7001_ $$aVan Hoecke, Sofie,$$eeditor. 001434654 77608 $$iPrint version:$$z9783030676698 001434654 77608 $$iPrint version:$$z9783030676711 001434654 830_0 $$aLecture notes in computer science.$$pLecture notes in artificial intelligence. 001434654 830_0 $$aLecture notes in computer science ;$$v12461. 001434654 852__ $$bebk 001434654 85640 $$3Springer Nature$$uhttps://univsouthin.idm.oclc.org/login?url=https://link.springer.com/10.1007/978-3-030-67670-4$$zOnline Access$$91397441.1 001434654 909CO $$ooai:library.usi.edu:1434654$$pGLOBAL_SET 001434654 980__ $$aBIB 001434654 980__ $$aEBOOK 001434654 982__ $$aEbook 001434654 983__ $$aOnline 001434654 994__ $$a92$$bISE