Projects funded by the NCN

Information on the principal investigator and host institution

Information of the project and the call

Keywords

Equipment

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SOSnet: sparse modelling and prediction for high-dimensional data.

2015/17/B/ST6/01878

Keywords:

high-dimensional data model selection sparse estimation Lasso

Descriptors:

  • ST6_11: Machine learning, statistical data processing and applications using signal processing (e.g. speech, image, video)
  • NZ2_7: Bioinformatics

Panel:

ST6 - Computer science and informatics: informatics and information systems, computer science, scientific computing, intelligent systems

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. Piotr Pokarowski 

Number of co-investigators in the project: 8

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

Amount awarded: 498 400 PLN

Project start date (Y-m-d): 2016-02-12

Project end date (Y-m-d): 2019-10-11

Project duration:: 44 months (the same as in the proposal)

Project status: Project settled

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.

Equipment purchased [PL]

  1. stacja robocza (6 000 PLN)
  2. laptop (4 000 PLN)

Information in the final report

  • Publication in academic press/journals (5)
  1. Plant response to N availability in permafrost-affected alpine wetlands in arid and semi-arid climate zones
    Authors:
    M. Mętrak, P. Pokarowski, M. Sulwiński, A. Altantsetseg and M. Suska-Malawska
    Academic press:
    Science of the Total Environment (rok: 2020, tom: 721, strony: 137791), Wydawca: ScienceDirect
    Status:
    Published
    DOI:
    10.1016/j.scitotenv.2020.137791 - link to the publication
  2. Sparse Estimation in Ising Model via Penalized Monte Carlo Methods
    Authors:
    B. Miasojedow and W. Rejchel
    Academic press:
    Journal of Machine Learning Research (rok: 2018, tom: 19(75), strony: 45317), Wydawca: JMLR, Inc. and Microtome Publishing (United States)
    Status:
    Published
    DOI:
    Brak - link to the publication
  3. Deleting and Merging Regressors with the DMRnet Package
    Authors:
    Agnieszka Sołtys and Piotr Pokarowski
    Academic press:
    Journal of Statistical Software , Wydawca: Foundation for Open Access Statistics
    Status:
    Submitted
    DOI:
    brak - link to the publication
  4. Improving Lasso for Model Selection and Prediction
    Authors:
    P. Pokarowski, W. Rejchel, A. Sołtys, M. Frej and J. Mielniczuk
    Academic press:
    Scandinavian Journal of Statistics , Wydawca: Foundation of the Scandinavian Journal of Statistics
    Status:
    Submitted
    DOI:
    brak - link to the publication
  5. Selection Consistency of Lasso-Based Procedures for Misspecified High-Dimensional Binary Model and Random Regressors
    Authors:
    Mariusz Kubkowski and Jan Mielniczuk
    Academic press:
    Entropy (rok: 2020, tom: 22(2), strony: 153), Wydawca: Multidisciplinary Digital Publishing Institute
    Status:
    Published
    DOI:
    10.3390/e22020153 - link to the publication

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