Minimum Divergence Methods in Statistical Machine Learning: From an Information Geometric Viewpoint
Gespeichert in:
| Hauptverfasser: | , |
|---|---|
| Format: | Elektronisch E-Book |
| Sprache: | English |
| Veröffentlicht: |
Tokyo
Springer Japan
2022
Tokyo Springer |
| Ausgabe: | 1st ed. 2022 |
| Schlagworte: | |
| Online-Zugang: | BTU01 FHD01 FHN01 FHR01 FKE01 FRO01 FWS01 FWS02 HTW01 TUM01 UBM01 UBT01 UBW01 UBY01 UEI01 UPA01 Volltext |
| Beschreibung: | 1 Online-Ressource (X, 221 p. 18 illus., 15 illus. in color) |
| ISBN: | 9784431569220 |
| DOI: | 10.1007/978-4-431-56922-0 |
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| indexdate | 2024-08-01T16:16:06Z |
| institution | BVB |
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| language | English |
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| publisher | Springer Japan Springer |
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| spellingShingle | Eguchi, Shinto Komori, Osamu Minimum Divergence Methods in Statistical Machine Learning From an Information Geometric Viewpoint Statistics in Engineering, Physics, Computer Science, Chemistry and Earth Sciences Statistical Theory and Methods Probability and Statistics in Computer Science Statistics Computer science—Mathematics Mathematical statistics |
| title | Minimum Divergence Methods in Statistical Machine Learning From an Information Geometric Viewpoint |
| title_auth | Minimum Divergence Methods in Statistical Machine Learning From an Information Geometric Viewpoint |
| title_exact_search | Minimum Divergence Methods in Statistical Machine Learning From an Information Geometric Viewpoint |
| title_exact_search_txtP | Minimum Divergence Methods in Statistical Machine Learning From an Information Geometric Viewpoint |
| title_full | Minimum Divergence Methods in Statistical Machine Learning From an Information Geometric Viewpoint by Shinto Eguchi, Osamu Komori |
| title_fullStr | Minimum Divergence Methods in Statistical Machine Learning From an Information Geometric Viewpoint by Shinto Eguchi, Osamu Komori |
| title_full_unstemmed | Minimum Divergence Methods in Statistical Machine Learning From an Information Geometric Viewpoint by Shinto Eguchi, Osamu Komori |
| title_short | Minimum Divergence Methods in Statistical Machine Learning |
| title_sort | minimum divergence methods in statistical machine learning from an information geometric viewpoint |
| title_sub | From an Information Geometric Viewpoint |
| topic | Statistics in Engineering, Physics, Computer Science, Chemistry and Earth Sciences Statistical Theory and Methods Probability and Statistics in Computer Science Statistics Computer science—Mathematics Mathematical statistics |
| topic_facet | Statistics in Engineering, Physics, Computer Science, Chemistry and Earth Sciences Statistical Theory and Methods Probability and Statistics in Computer Science Statistics Computer science—Mathematics Mathematical statistics |
| url | https://doi.org/10.1007/978-4-431-56922-0 |
| work_keys_str_mv | AT eguchishinto minimumdivergencemethodsinstatisticalmachinelearningfromaninformationgeometricviewpoint AT komoriosamu minimumdivergencemethodsinstatisticalmachinelearningfromaninformationgeometricviewpoint |