國立虎尾科技大學 |

Machine Learning and Knowledge Discovery in Databases. Applied Data Science and Demo Track = European Conference, ECML PKDD 2020, Ghent, Belgium, September 14–18, 2020, Proceedings, Part V /

Record Type:	Language materials, printed : Monograph/item
Title/Author:	Machine Learning and Knowledge Discovery in Databases. Applied Data Science and Demo Track/ edited by Yuxiao Dong, Georgiana Ifrim, Dunja Mladenić, Craig Saunders, Sofie Van Hoecke.
Reminder of title:	European Conference, ECML PKDD 2020, Ghent, Belgium, September 14–18, 2020, Proceedings, Part V /
other author:	Dong, Yuxiao.
Description:	XLII, 577 p. 205 illus., 181 illus. in color.online resource. :
Contained By:	Springer Nature eBook
Subject:	Data mining. -
Online resource:	https://doi.org/10.1007/978-3-030-67670-4
ISBN:	9783030676704

Machine Learning and Knowledge Discovery in Databases. Applied Data Science and Demo Track = European Conference, ECML PKDD 2020, Ghent, Belgium, September 14–18, 2020, Proceedings, Part V /
Machine Learning and Knowledge Discovery in Databases. Applied Data Science and Demo TrackEuropean Conference, ECML PKDD 2020, Ghent, Belgium, September 14–18, 2020, Proceedings, Part V /[electronic resource] :edited by Yuxiao Dong, Georgiana Ifrim, Dunja Mladenić, Craig Saunders, Sofie Van Hoecke. - 1st ed. 2021. - XLII, 577 p. 205 illus., 181 illus. in color.online resource. - Lecture Notes in Artificial Intelligence ;12461. - Lecture Notes in Artificial Intelligence ;9285.

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.

The 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. .

ISBN: 9783030676704

Standard No.: 10.1007/978-3-030-67670-4doiSubjects--Topical Terms:

528622
Data mining.

LC Class. No.: QA76.9.D343

Dewey Class. No.: 006.312

Machine Learning and Knowledge Discovery in Databases. Applied Data Science and Demo Track = European Conference, ECML PKDD 2020, Ghent, Belgium, September 14–18, 2020, Proceedings, Part V /
LDR:03923nam a22004215i 4500 001 1047948
003 DE-He213
005 20211013095354.0
007 cr nn 008mamaa
008 220103s2021 sz | s |||| 0|eng d
020 $a 9783030676704 $9 978-3-030-67670-4
024 7 $a 10.1007/978-3-030-67670-4 $2 doi
035 $a 978-3-030-67670-4
050 4 $a QA76.9.D343
072 7 $a UNF $2 bicssc
072 7 $a COM021030 $2 bisacsh
072 7 $a UNF $2 thema
072 7 $a UYQE $2 thema
082 0 4 $a 006.312 $2 23
245 1 0 $a Machine Learning and Knowledge Discovery in Databases. Applied Data Science and Demo Track $h [electronic resource] : $b European Conference, ECML PKDD 2020, Ghent, Belgium, September 14–18, 2020, Proceedings, Part V / $c edited by Yuxiao Dong, Georgiana Ifrim, Dunja Mladenić, Craig Saunders, Sofie Van Hoecke.
250 $a 1st ed. 2021.
264 1 $a Cham : $b Springer International Publishing : $b Imprint: Springer, $c 2021.
300 $a XLII, 577 p. 205 illus., 181 illus. in color. $b online resource.
336 $a text $b txt $2 rdacontent
337 $a computer $b c $2 rdamedia
338 $a online resource $b cr $2 rdacarrier
347 $a text file $b PDF $2 rda
490 1 $a Lecture Notes in Artificial Intelligence ; $v 12461
505 0 $a 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.
520 $a The 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. .
650 0 $a Data mining. $3 528622
650 0 $a Machine learning. $3 561253
650 0 $a Education—Data processing. $3 1253610
650 0 $a Application software. $3 528147
650 0 $a Computer organization. $3 596298
650 1 4 $a Data Mining and Knowledge Discovery. $3 677765
650 2 4 $a Machine Learning. $3 1137723
650 2 4 $a Computers and Education. $3 669806
650 2 4 $a Computer Appl. in Social and Behavioral Sciences. $3 669920
650 2 4 $a Computer Systems Organization and Communication Networks. $3 669309
700 1 $a Dong, Yuxiao. $e editor. $4 edt $4 http://id.loc.gov/vocabulary/relators/edt $3 1349454
700 1 $a Ifrim, Georgiana. $e editor. $1 https://orcid.org/0000-0002-8400-2972 $4 edt $4 http://id.loc.gov/vocabulary/relators/edt $3 1302442
700 1 $a Mladenić, Dunja. $e editor. $4 edt $4 http://id.loc.gov/vocabulary/relators/edt $3 1268019
700 1 $a Saunders, Craig. $e editor. $4 edt $4 http://id.loc.gov/vocabulary/relators/edt $3 1349455
700 1 $a Van Hoecke, Sofie. $e editor. $4 edt $4 http://id.loc.gov/vocabulary/relators/edt $3 1351701
710 2 $a SpringerLink (Online service) $3 593884
773 0 $t Springer Nature eBook
776 0 8 $i Printed edition: $z 9783030676698
776 0 8 $i Printed edition: $z 9783030676711
830 0 $a Lecture Notes in Artificial Intelligence ; $v 9285 $3 1253845
856 4 0 $u https://doi.org/10.1007/978-3-030-67670-4
912 $a ZDB-2-SCS
912 $a ZDB-2-SXCS
912 $a ZDB-2-LNC
950 $a Computer Science (SpringerNature-11645)
950 $a Computer Science (R0) (SpringerNature-43710)