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@InProceedings{krivosija_et_al:LIPIcs:2019:10451, author = {Amer Krivosija and Alexander Munteanu}, title = {{Probabilistic Smallest Enclosing Ball in High Dimensions via Subgradient Sampling}}, booktitle = {35th International Symposium on Computational Geometry (SoCG 2019)}, pages = {47:1--47:14}, series = {Leibniz International Proceedings in Informatics (LIPIcs)}, ISBN = {978-3-95977-104-7}, ISSN = {1868-8969}, year = {2019}, volume = {129}, editor = {Gill Barequet and Yusu Wang}, publisher = {Schloss Dagstuhl--Leibniz-Zentrum fuer Informatik}, address = {Dagstuhl, Germany}, URL = {http://drops.dagstuhl.de/opus/volltexte/2019/10451}, URN = {urn:nbn:de:0030-drops-104515}, doi = {10.4230/LIPIcs.SoCG.2019.47}, annote = {Keywords: geometric median, convex optimization, smallest enclosing ball, probabilistic data, support vector data description, kernel methods} }
Keywords: | geometric median, convex optimization, smallest enclosing ball, probabilistic data, support vector data description, kernel methods | |
Seminar: | 35th International Symposium on Computational Geometry (SoCG 2019) | |
Issue date: | 2019 | |
Date of publication: | 11.06.2019 |