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Efficiently Computable Safety Bounds for Gaussian Processes in Active Learning

; ; ; ;

In
International Conference on Artificial Intelligence and Statistics, 2-4 May 2024, Palau de Congressos, Valencia, Spain / Editors: Sanjoy Dasgupta, Stephan Mandt, Yingzhen Li, Seiten/Artikel-Nr: 1333-1341

Konferenz/Event:27. International Conference on Artificial Intelligence and Statistics , Valenica , Spain , AISTATS 2024 , 2024-05-02 - 2024-05-04

: MLResearchPress

Umfang1333-1341

ReiheProceedings of machine learning research ; 238

Online
URL: https://proceedings.mlr.press/v238/
URL: https://proceedings.mlr.press/v238/tebbe24a/tebbe24a.pdf

Einrichtungen

  1. Lehrstuhl für Stochastik und Institut für Statistik und Wirtschaftsmathematik (116110)
  2. Fachgruppe Mathematik (110000)


External links:
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Dokumenttyp
Contribution to a book/Contribution to a conference proceedings

Format
online

Sprache
English

Anmerkung
Peer review status of article unknown

Externe Identnummern
SCOPUS: SCOPUS:2-s2.0-85194147371
WOS Core Collection: WOS:001221034004001

Interne Identnummern
RWTH-2024-09399
Datensatz-ID: 994587

Beteiligte Länder
Germany, Netherlands

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Faculty of Mathematics and Natural Sciences (Fac.1) > Department of Mathematics
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110000
116110

 Record created 2024-10-07, last modified 2025-10-10


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