Proceedings of the 2021 SIAM International Conference on Data Mining (SDM):
Data mining is an important tool in science, engineering, industrial processes, healthcare, business, and medicine. The datasets in these fields are large, complex, and often noisy. Extracting knowledge requires the use of sophisticated, high performance and principled analysis techniques and algori...
Gespeichert in:
| Weitere Verfasser: | , |
|---|---|
| Format: | Elektronisch Tagungsbericht E-Book |
| Sprache: | English |
| Veröffentlicht: |
Philadelphia, Pennsylvania
Society for Industrial and Applied Mathematics, SIAM
[2021]
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| Schlagworte: | |
| Online-Zugang: | TUM01 UBW01 UBY01 UER01 Volltext |
| Zusammenfassung: | Data mining is an important tool in science, engineering, industrial processes, healthcare, business, and medicine. The datasets in these fields are large, complex, and often noisy. Extracting knowledge requires the use of sophisticated, high performance and principled analysis techniques and algorithms, based on sound theoretical and statistical foundations. These techniques in turn require implementations that are carefully tuned for performance; powerful visualization technologies; interface systems that are usable by scientists, engineers, and physicians as well as researchers; and infrastructures that support them. This conference provides a venue for researchers who are addressing these problems to present their work in a peer-reviewed forum. It also provides an ideal setting for graduate students and others new to the field to learn about cutting-edge research by hearing outstanding invited speakers and attending presentations and tutorials (included with conference registration). A set of focused workshops are also held on the last day of the conference. The proceedings of the conference arepublished in archival form, and are also made available on the SIAM web site |
| Beschreibung: | 1 Online-Ressource (764 Seiten) |
| ISBN: | 1611976235 9781611976700 |
| DOI: | 10.1137/1.9781611976700 |
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| spelling | Proceedings of the 2021 SIAM International Conference on Data Mining (SDM) Carlotta Demeniconi ; Ian Davidson, editors SIAM 2021 International Conference on Data Mining Philadelphia, Pennsylvania Society for Industrial and Applied Mathematics, SIAM [2021] © 2021 1 Online-Ressource (764 Seiten) txt rdacontent c rdamedia cr rdacarrier Data mining is an important tool in science, engineering, industrial processes, healthcare, business, and medicine. The datasets in these fields are large, complex, and often noisy. Extracting knowledge requires the use of sophisticated, high performance and principled analysis techniques and algorithms, based on sound theoretical and statistical foundations. These techniques in turn require implementations that are carefully tuned for performance; powerful visualization technologies; interface systems that are usable by scientists, engineers, and physicians as well as researchers; and infrastructures that support them. This conference provides a venue for researchers who are addressing these problems to present their work in a peer-reviewed forum. It also provides an ideal setting for graduate students and others new to the field to learn about cutting-edge research by hearing outstanding invited speakers and attending presentations and tutorials (included with conference registration). A set of focused workshops are also held on the last day of the conference. The proceedings of the conference arepublished in archival form, and are also made available on the SIAM web site Data mining / Congresses Data mining ; Congresses Discrete mathematics and graph theory (DE-588)1071861417 Konferenzschrift gnd-content Demeniconi, Carlotta edt Davidson, Ian edt SIAM International Conference on Data Mining 2021 Online Sonstige (DE-588)1251341705 oth Erscheint auch als Druck-Ausgabe 1-61197-623-5 https://doi.org/10.1137/1.9781611976700 Verlag URL des Erstveröffentlichers Volltext |
| spellingShingle | Proceedings of the 2021 SIAM International Conference on Data Mining (SDM) |
| subject_GND | (DE-588)1071861417 |
| title | Proceedings of the 2021 SIAM International Conference on Data Mining (SDM) |
| title_alt | SIAM 2021 International Conference on Data Mining |
| title_auth | Proceedings of the 2021 SIAM International Conference on Data Mining (SDM) |
| title_exact_search | Proceedings of the 2021 SIAM International Conference on Data Mining (SDM) |
| title_exact_search_txtP | Proceedings of the 2021 SIAM International Conference on Data Mining (SDM) |
| title_full | Proceedings of the 2021 SIAM International Conference on Data Mining (SDM) Carlotta Demeniconi ; Ian Davidson, editors |
| title_fullStr | Proceedings of the 2021 SIAM International Conference on Data Mining (SDM) Carlotta Demeniconi ; Ian Davidson, editors |
| title_full_unstemmed | Proceedings of the 2021 SIAM International Conference on Data Mining (SDM) Carlotta Demeniconi ; Ian Davidson, editors |
| title_short | Proceedings of the 2021 SIAM International Conference on Data Mining (SDM) |
| title_sort | proceedings of the 2021 siam international conference on data mining sdm |
| topic_facet | Konferenzschrift |
| url | https://doi.org/10.1137/1.9781611976700 |
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