000 | 05110nam a22006615i 4500 | ||
---|---|---|---|
001 | 978-3-030-67658-2 | ||
003 | DE-He213 | ||
005 | 20240730180602.0 | ||
007 | cr nn 008mamaa | ||
008 | 210224s2021 sz | s |||| 0|eng d | ||
020 |
_a9783030676582 _9978-3-030-67658-2 |
||
024 | 7 |
_a10.1007/978-3-030-67658-2 _2doi |
|
050 | 4 | _aQA76.9.D343 | |
072 | 7 |
_aUNF _2bicssc |
|
072 | 7 |
_aUYQE _2bicssc |
|
072 | 7 |
_aCOM021030 _2bisacsh |
|
072 | 7 |
_aUNF _2thema |
|
072 | 7 |
_aUYQE _2thema |
|
082 | 0 | 4 |
_a006.312 _223 |
245 | 1 | 0 |
_aMachine Learning and Knowledge Discovery in Databases _h[electronic resource] : _bEuropean Conference, ECML PKDD 2020, Ghent, Belgium, September 14-18, 2020, Proceedings, Part I / _cedited by Frank Hutter, Kristian Kersting, Jefrey Lijffijt, Isabel Valera. |
250 | _a1st ed. 2021. | ||
264 | 1 |
_aCham : _bSpringer International Publishing : _bImprint: Springer, _c2021. |
|
300 |
_aL, 764 p. 219 illus., 188 illus. in color. _bonline resource. |
||
336 |
_atext _btxt _2rdacontent |
||
337 |
_acomputer _bc _2rdamedia |
||
338 |
_aonline resource _bcr _2rdacarrier |
||
347 |
_atext file _bPDF _2rda |
||
490 | 1 |
_aLecture Notes in Artificial Intelligence, _x2945-9141 ; _v12457 |
|
505 | 0 | _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. | |
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. . | ||
650 | 0 |
_aData mining. _93907 |
|
650 | 0 |
_aData structures (Computer science). _98188 |
|
650 | 0 |
_aInformation theory. _914256 |
|
650 | 0 |
_aMachine learning. _91831 |
|
650 | 0 |
_aSocial sciences _xData processing. _983360 |
|
650 | 0 |
_aComputer vision. _9120891 |
|
650 | 1 | 4 |
_aData Mining and Knowledge Discovery. _9120892 |
650 | 2 | 4 |
_aData Structures and Information Theory. _931923 |
650 | 2 | 4 |
_aMachine Learning. _91831 |
650 | 2 | 4 |
_aComputer Application in Social and Behavioral Sciences. _931815 |
650 | 2 | 4 |
_aComputer Vision. _9120893 |
700 | 1 |
_aHutter, Frank. _eeditor. _4edt _4http://id.loc.gov/vocabulary/relators/edt _9120894 |
|
700 | 1 |
_aKersting, Kristian. _eeditor. _4edt _4http://id.loc.gov/vocabulary/relators/edt _9120895 |
|
700 | 1 |
_aLijffijt, Jefrey. _eeditor. _4edt _4http://id.loc.gov/vocabulary/relators/edt _9120896 |
|
700 | 1 |
_aValera, Isabel. _eeditor. _4edt _4http://id.loc.gov/vocabulary/relators/edt _9120897 |
|
710 | 2 |
_aSpringerLink (Online service) _9120898 |
|
773 | 0 | _tSpringer Nature eBook | |
776 | 0 | 8 |
_iPrinted edition: _z9783030676575 |
776 | 0 | 8 |
_iPrinted edition: _z9783030676599 |
830 | 0 |
_aLecture Notes in Artificial Intelligence, _x2945-9141 ; _v12457 _9120899 |
|
856 | 4 | 0 | _uhttps://doi.org/10.1007/978-3-030-67658-2 |
912 | _aZDB-2-SCS | ||
912 | _aZDB-2-SXCS | ||
912 | _aZDB-2-LNC | ||
942 | _cELN | ||
999 |
_c90395 _d90395 |