Projects funded by the NCN

Information on the principal investigator and host institution

Information of the project and the call

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Monte Carlo methods for Markov jump processes.

2015/17/D/ST1/01198

Keywords:

Monte Carlo methods Hidden Markov Models Continuous Time Bayesian Networks

Descriptors:

  • ST1_13: Probability and statistics
  • ST1_18: Control theory and optimisation
  • 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 Błażej Miasojedow 

Number of co-investigators in the project: 1

Call: SONATA 9 - announced on 2015-03-16

Amount awarded: 93 600 PLN

Project start date (Y-m-d): 2016-02-15

Project end date (Y-m-d): 2019-02-14

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

Project status: Project settled

Project description

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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 (3)
  1. Sparse Estimation in Ising Model via Penalized Monte Carlo Methods
    Authors:
    Błażej Miasojedow, Wojciech Rejchel
    Academic press:
    Journal of Machine Learning Research (rok: 2018, tom: 19(75), strony: 45317), Wydawca: MICROTOME PUBL
    Status:
    Published
    DOI:
    brak - link to the publication
  2. Geometric ergodicity of Rao and Teh's algorithm for Markov jump processes and CTBNs
    Authors:
    Błażej Miasojedow, Wojciech Niemiro
    Academic press:
    Electronic Journal of Statistics (rok: 2017, tom: 11(2), strony: 4629-4648), Wydawca: Institute of Mathematical Statistics
    Status:
    Published
    DOI:
    10.1214/17-EJS1348 - link to the publication
  3. Analysis of Langevin Monte Carlo via Convex Optimization
    Authors:
    Alain Durmus, Szymon Majewski, Błażej Miasojedow
    Academic press:
    Journal of Machine Learning Research (rok: 2019, tom: 20, strony: 16803), Wydawca: MICROTOME PUBL
    Status:
    Published
    DOI:
    brak - link to the publication

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