Tatjana Pavlenko
Professor vid Statistiska institutionen
- E-post:
- tatjana.pavlenko@statistik.uu.se
- Besöksadress:
- Ekonomikum (plan 3)
Kyrkogårdsgatan 10 - Postadress:
- Box 513
751 20 UPPSALA
Ladda ned kontaktuppgifter för Tatjana Pavlenko vid Statistiska institutionen
Kort presentation
Tatjana Pavlenko's research interests lie in the area of applied probability and statistical inference in high and infinite dimensions, computational statistics - especially Bayesian graph structure learning, high-dimensional problems in statistical machine learning, detection and identification of sparse signals, with applications to large-scale biomedical data.
Google scholar link
Nyckelord
- high-dimensional statistical inference
- statistical machine learning
- sparse signal detection
- large-scale biomedical data
- multivariate data more broadly
Publikationer
Senaste publikationer
A Behrens-Fisher problem for general factor models in high dimensions
Ingår i Journal of Multivariate Analysis, 2023
Adaptive threshold-based classification of sparse high-dimensional data
Ingår i Electronic Journal of Statistics, s. 1952-1996, 2022
- DOI för Adaptive threshold-based classification of sparse high-dimensional data
- Ladda ner fulltext (pdf) av Adaptive threshold-based classification of sparse high-dimensional data
Sequential sampling of junction trees for decomposable graphs
Ingår i Statistics and computing, 2022
- DOI för Sequential sampling of junction trees for decomposable graphs
- Ladda ner fulltext (pdf) av Sequential sampling of junction trees for decomposable graphs
Alla publikationer
Artiklar i tidskrift
A Behrens-Fisher problem for general factor models in high dimensions
Ingår i Journal of Multivariate Analysis, 2023
Adaptive threshold-based classification of sparse high-dimensional data
Ingår i Electronic Journal of Statistics, s. 1952-1996, 2022
- DOI för Adaptive threshold-based classification of sparse high-dimensional data
- Ladda ner fulltext (pdf) av Adaptive threshold-based classification of sparse high-dimensional data
Sequential sampling of junction trees for decomposable graphs
Ingår i Statistics and computing, 2022
- DOI för Sequential sampling of junction trees for decomposable graphs
- Ladda ner fulltext (pdf) av Sequential sampling of junction trees for decomposable graphs