Projects funded by the NCN

Information on the principal investigator and host institution

Information of the project and the call

Keywords

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Computational methods for high dimensional statistical learning

2018/31/B/ST1/00253

Keywords:

Monte Carlo methods sparse modelling stochastic approximation Langevin Monte Carlo multilabel classification Bayesian networks

Descriptors:

  • ST1_13: Probability and statistics
  • ST1_17: Applied mathematics
  • ST6_11: Machine learning, statistical data processing and applications using signal processing (e.g. speech, image, video)

Panel:

ST1 - Mathematics: all areas of mathematics, pure and applied, as well as mathematical foundations of computer science, physics and statistics

Host institution :

Uniwersytet Warszawski, Wydział Matematyki, Informatyki i Mechaniki

woj. mazowieckie

Other projects carried out by the institution 

Principal investigator (from the host institution):

dr hab. Błażej Miasojedow 

Number of co-investigators in the project: 5

Call: OPUS 16 - announced on 2018-09-14

Amount awarded: 663 600 PLN

Project start date (Y-m-d): 2019-07-04

Project end date (Y-m-d): 2024-07-03

Project duration:: 36 months (the same as in the proposal)

Project status: Pending project

Project description

Download the project description in a pdf file

Note - project descriptions were prepared by the authors of the applications themselves and placed in the system in an unchanged form.

Information in the final report

  • Publication in academic press/journals (5)
  • Articles in post-conference publications (3)
  1. CONET: copy number event tree model of evolutionary tumor history for single-cell data
    Authors:
    Magda Markowska, Tomasz Cąkała, Błażej Miasojedow, Bogac Aybey, Dilafruz Juraeva, Johanna Mazur, Edith Ross, Eike Staub, Ewa Szczurek
    Academic press:
    Genome Biology (rok: 2022, tom: 23, strony: 128), Wydawca: BMC
    Status:
    Published
    DOI:
    10.1186/s13059-022-02693-z - link to the publication
  2. Adaptive Bayesian SLOPE: Model Selection With Incomplete Data
    Authors:
    Wei Jiang , Małgorzata Bogdan , Julie Josse ,Szymon Majewski , Błażej Miasojedow, Veronika Ročková & TraumaBase® Group
    Academic press:
    Journal of Computational and Graphical Statistics (rok: 2022, tom: 31, strony: 113-137), Wydawca: Taylor and Francis
    Status:
    Published
    DOI:
    10.1080/10618600.2021.1963263 - link to the publication
  3. Particle MCMC With Poisson Resampling: Parallelization and Continuous Time Models
    Authors:
    Tomasz Ca̧kała , Błażej Miasojedow, Wojciech Niemiro
    Academic press:
    Journal of Computational and Graphical Statistics (rok: 2021, tom: 30, strony: 671-684), Wydawca: Taylor and Francis
    Status:
    Published
    DOI:
    10.1080/10618600.2020.1840998 - link to the publication
  4. Absence and presence of Lavrentiev's phenomenon for double phase functionals upon every choice of exponents
    Authors:
    Michał Borowski, Iwona Chlebicka, Filomena De Filippis, Błażej Miasojedow
    Academic press:
    Calculus of Variations and Partial Differential Equations (rok: 2024, tom: 2,64930555555556, strony: 45314), Wydawca: Sringer
    Status:
    Published
    DOI:
    10.1007/s00526-023-02640-1 - link to the publication
  5. Critical assessment of synthetic accessibility scores in computer-assisted synthesis planning
    Authors:
    Grzegorz Skoraczyński, Mateusz Kitlas, Błażej Miasojedow, Anna Gambin
    Academic press:
    Journal of Cheminformatics (rok: 2023, tom: 15, strony: 6), Wydawca: BMC
    Status:
    Published
    DOI:
    10.1186/s13321-023-00678-z - link to the publication
  1. Asymptotic Guarantees for Learning Generative Models with the Sliced-Wasserstein Distance
    Authors:
    Kimia Nadjahi, Alain Durmus, Umut Simsekli, Roland Badeau
    Conference:
    Advances in Neural Information Processing Systems 32 (NeurIPS 2019) (rok: 2019, ), Wydawca: Advances in Neural Information Processing Systems
    Data:
    konferencja 8-14.12.2019
    Status:
    Published
    DOI:
    link to the publication
  2. Double Logistic Regression Approach to Biased Positive-Unlabeled Data
    Authors:
    Konrad Furmańczyk, Jan Mielniczuk, Wojciech Rejchel, Paweł Teisseyre
    Conference:
    26th European Conference on Artificial Intelligence ECAI 2023 (rok: 2023, ), Wydawca: IOS Press
    Data:
    konferencja 30.09-4.10.2023
    Status:
    Published
  3. Copula-like Variational Inference
    Authors:
    Marcel Hirt, Petros Dellaportas, Alain Durmus
    Conference:
    Advances in Neural Information Processing Systems 32 (NeurIPS 2019) (rok: 2019, ), Wydawca: Advances in Neural Information Processing Systems
    Data:
    konferencja 8-14.12.2019
    Status:
    Published
    DOI:
    link to the publication

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