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Publication profile

Publication profile

Martin Tveten

Martin, Tveten
Name: Martin Tveten
Title: Forsker / Research Scientist
Phone: (+47) +47 22 85 25 80 Mob: +47 988 42 616
Email: tveten [at] nr [dot] no
Scientific areas: Statistical analysis
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Academic article
2021
Hellton, Kristoffer Herland; Tveten, Martin; Stakkeland, Morten; Engebretsen, Solveig; Haug, Ola; Aldrin, Magne Tommy. Real-time prediction of propulsion motor overheating using machine learning. Journal of Marine Engineering & Technology (ISSN 2046-4177). doi: 10.1080/20464177.2021.1978745. 2021. Arkiv
2019
Moss, Jonas; Tveten, Martin. kdensity: An R package for kernel density estimation with parametric starts and asymmetric kernels. Journal of Open Source Software (JOSS) (ISSN 2475-9066). doi: 10.21105/joss.01566. 2019. Arkiv
Tveten, Martin. Which principal components are most sensitive in the change detection problem? Stat (ISSN 2049-1573). 8(1) doi: 10.1002/sta4.252. 2019. Arkiv
Academic lecture
2021
Tveten, Martin. Introduction to change detection. Friday AI Webinar; Digitalt, 9/24/2021.
Tveten, Martin. Scalable changepoint and anomaly detection in cross-correlated data. Simula@BI; Digitalt, 5/20/2021.
Tveten, Martin. Scalable changepoint and anomaly detection in cross-correlated data. StatScale workshop 2021, 4/22/2021 - 4/23/2021.
2019
Tveten, Martin. Online detection of sparse changes in high-dimensional data streams using tailored projections. European Meeting of Statisticians 2019, 7/22/2019 - 7/26/2019.
2018
Tveten, Martin. Tailoring PCA for detecting sparse changes in multi-stream data. Big Insight Day, 10/29/2018.
2017
Tveten, Martin; Brandsæter, Andreas; Glad, Ingrid Kristine. Anomaly detection in maritime data streams. European Network for Business and Industrial Statistics ENBIS 2017; University of Naples Umberto II, 9/12/2017.
Poster
2018
Tveten, Martin. Tailoring PCA for detecting sparse changes in multi-stream data. Joint Statistical Meeting 2018, 7/28/2018 - 8/2/2018.
Doctoral dissertation
2021
Tveten, Martin. Scalable change and anomaly detection in cross-correlated data. Universitetet i Oslo. pp 161. 2021. Arkiv
Report
2019
Tveten, Martin; Glad, Ingrid Kristine. Online Detection of Sparse Changes in High-Dimensional Data Streams Using Tailored Projections. arXiv. pp 26. 2019. Fulltekst
Popular scientific lecture
2019
Tveten, Martin. Å studere matematikk ved UiO. Fagdager på Matematisk insitutt, 2/26/2019 - 3/12/2019.
Programme management
2022
Løland, Anders; Tveten, Martin; Moen, Per August Jarval. Episode 15: Krafthack 2022: Suksess med Rema 1000-strategi. 2022. Fulltekst
2021
Løland, Anders; Tveten, Martin. Episode 9: Hvordan kan vi oppdage katastrofale avvik? Med gjest Martin Tveten. 2021. Fulltekst
Postal address:
Norsk Regnesentral/
Norwegian Computing Center
P.O. Box 114 Blindern
NO-0314 Oslo
Norway
Visit address:
Norsk Regnesentral
Gaustadalleen 23a
Kristen Nygaards hus
NO-0373 Oslo.
Phone:
(+47) 22 85 25 00
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Postal address: Norsk Regnesentral/Norwegian Computing Center, P.O. Box 114 Blindern, NO-0314 Oslo, Norway
Visit address: Norsk Regnesentral, Gaustadalleen 23a, Kristen Nygaards hus, NO-0373 Oslo.
Phone: (+47) 22 85 25 00
AddressHow to get to NR