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Berent Ånund Strømnes Lundes bilde

Berent Ånund Strømnes Lunde

Førsteamanuensis
  • E-postBerent.Lunde@uib.no
  • Besøksadresse
    Realfagbygget, Allégaten 41
  • Postadresse
    Postboks 7803
    5020 Bergen

Machine learning / Information theory / Computational statistics

I develop information theory for algorithms in machine learning and computational statistics. My conjecture is that, through a deeper understanding of the mathematical and statistical properties of ML-algorithms, it is possible to device smarter and more data- and information-adaptive ML-algorithms. Currently I work on theory and methods to avoid all types of manual tuning in gradient tree boosting-type methods.

Mathmatical finance / Actuarial mathematics

I seek more extensive usage of machine learning and advanced statistical modelling in the applied actuarial field. I believe a competetive market will require the industry to capitalize on modern statistical methodology, and see methods work in symbiosis on both risk-assessments, customer behaviour and more, to optimize value for stakeholders. To this end, the methods needs to be safe and understandable for practitioners to apply, and robustly implemented for production environments.

Faglig foredrag
  • Vis forfatter(e) 2018. Boosting i forsikring.
Vitenskapelig foredrag
  • Vis forfatter(e) 2019. Information criteria for gradient boosted trees: Adaptive tree size and early stopping.
  • Vis forfatter(e) 2019. An information criterion for gradient boosted trees.
  • Vis forfatter(e) 2019. An information criterion for gradient boosted trees.
  • Vis forfatter(e) 2018. Saddlepoint adjusted inversion of characteristic functions.
  • Vis forfatter(e) 2018. Information efficient gradient tree boosting.
  • Vis forfatter(e) 2018. Information efficient gradient tree boosting.
  • Vis forfatter(e) 2018. Finance in the frequency domain.
  • Vis forfatter(e) 2017. Likelihood Estimation of Jump-Diffusions: Extensions from Diffusions to Jump-Diffusions, Implementation with Automatic Differentiation, and Applications.
Mastergradsoppgave
  • Vis forfatter(e) 2016. Likelihood Estimation of Jump-Diffusions: Extensions from Diffusions to Jump-Diffusions, Implementation with Automatic Differentiation, and Applications.

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