LEADER 05089nam 22006975 450 001 9910484810503321 005 20221012203717.0 010 $a3-030-67670-6 024 7 $a10.1007/978-3-030-67670-4 035 $a(CKB)4100000011781545 035 $a(MiAaPQ)EBC6501093 035 $a(DE-He213)978-3-030-67670-4 035 $a(PPN)253858453 035 $a(EXLCZ)994100000011781545 100 $a20210224d2021 u| 0 101 0 $aeng 135 $aurnn|008mamaa 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aMachine Learning and Knowledge Discovery in Databases. Applied Data Science and Demo Track $eEuropean Conference, ECML PKDD 2020, Ghent, Belgium, September 14?18, 2020, Proceedings, Part V /$fedited by Yuxiao Dong, Georgiana Ifrim, Dunja Mladeni?, Craig Saunders, Sofie Van Hoecke 205 $a1st ed. 2021. 210 1$aCham :$cSpringer International Publishing :$cImprint: Springer,$d2021. 215 $a1 online resource (XLII, 577 p. 205 illus., 181 illus. in color.) 225 1 $aLecture Notes in Artificial Intelligence,$x2945-9141 ;$v12461 311 $a3-030-67669-2 327 $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. 330 $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. . 410 0$aLecture Notes in Artificial Intelligence,$x2945-9141 ;$v12461 606 $aData mining 606 $aMachine learning 606 $aEducation?Data processing 606 $aSocial sciences?Data processing 606 $aComputer engineering 606 $aComputer networks 606 $aData Mining and Knowledge Discovery 606 $aMachine Learning 606 $aComputers and Education 606 $aComputer Application in Social and Behavioral Sciences 606 $aComputer Engineering and Networks 615 0$aData mining. 615 0$aMachine learning. 615 0$aEducation?Data processing. 615 0$aSocial sciences?Data processing. 615 0$aComputer engineering. 615 0$aComputer networks. 615 14$aData Mining and Knowledge Discovery. 615 24$aMachine Learning. 615 24$aComputers and Education. 615 24$aComputer Application in Social and Behavioral Sciences. 615 24$aComputer Engineering and Networks. 676 $a006.312 702 $aDong$b Yuxiao$4edt$4http://id.loc.gov/vocabulary/relators/edt 702 $aIfrim$b Georgiana$4edt$4http://id.loc.gov/vocabulary/relators/edt 702 $aMladeni?$b Dunja$4edt$4http://id.loc.gov/vocabulary/relators/edt 702 $aSaunders$b Craig$4edt$4http://id.loc.gov/vocabulary/relators/edt 702 $aVan Hoecke$b Sofie$4edt$4http://id.loc.gov/vocabulary/relators/edt 906 $aBOOK 912 $a9910484810503321 996 $aMachine Learning and Knowledge Discovery in Databases$93568347 997 $aUNINA