Projects funded by the NCN

Information on the principal investigator and host institution

Information of the project and the call

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Consistent and scalable learning algorithms for structured output prediction

2013/09/D/ST6/03917

Keywords:

machine learning structured ouput prediction statistical consistency risk minimization large-scale learning algorithms

Descriptors:

  • ST6_11: Machine learning, statistical data processing and applications using signal processing (e.g. speech, image, video)
  • ST6_7: Artificial intelligence, intelligent systems, multi-agent systems

Panel:

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

Host institution :

Politechnika Poznańska, Wydział Informatyki

woj. wielkopolskie

Other projects carried out by the institution 

Principal investigator (from the host institution):

dr Krzysztof Dembczyński 

Number of co-investigators in the project: 2

Call: SONATA 5 - announced on 2013-03-15

Amount awarded: 393 900 PLN

Project start date (Y-m-d): 2014-03-24

Project end date (Y-m-d): 2017-03-23

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

Project status: Project settled

Information in the final report

  • Publication in academic press/journals (4)
  • Articles in post-conference publications (3)
  • Book publications / chapters in book publications (1)
  1. Surrogate regret bounds for generalized classification performance metrics
    Authors:
    Wojciech Kotlowski, Krzysztof Dembczynski
    Academic press:
    Machine Learning (rok: 2017, tom: 106, strony: 549-572), Wydawca: Springer
    Status:
    Published
    DOI:
    10.1007/s10994-016-5591-7 - link to the publication
  2. Exact and efficient top-K inference for multi-target prediction by querying separable linear relational models
    Authors:
    Michiel Stock, Krzysztof Dembczyński, Bernard De Baets, Willem Waegeman
    Academic press:
    Data Mining and Knowledge Discovery (rok: 2016, ), Wydawca: Springer
    Status:
    Accepted for publication
    DOI:
    10.1007/s10618-016-0456-z - link to the publication
  3. Extreme classification under limited space and time budget
    Authors:
    Kalina Jasinska, Krzysztof Dembczyński
    Academic press:
    Schedae Informaticae (rok: 2016, tom: 25, strony: 45558), Wydawca: Uniwersytet Jagielloński
    Status:
    Published
    DOI:
    10.4467/20838476SI.16.001.6182 - link to the publication
  4. Multi-target prediction: a unifying view on problems and methods
    Authors:
    Willem Waegeman, Krzysztof Dembczyński, Eyke Hüllermeier
    Academic press:
    Data Mining and Knowledge Discovery (rok: 2019, tom: 33, strony: 293–324), Wydawca: Springer
    Status:
    Published
    DOI:
    10.1007/s10618-018-0595-5 - link to the publication
  1. Online F-Measure Optimization
    Authors:
    Róbert Busa-Fekete, Balázs Szörényi, Krzysztof Dembczyński, Eyke Hüllermeier
    Conference:
    Advances in Neural Information Processing Systems 28 (NIPS 2015) (rok: 2015, ), Wydawca: Curran Associates, Inc.
    Data:
    konferencja 7-12/12/2015
    Status:
    Published
    DOI:
    link to the publication
  2. Surrogate regret bounds for generalized classification performance metrics
    Authors:
    Wojciech Kotłowski, Krzysztof Dembczyński
    Conference:
    Asian Conference on Machine Learning (rok: 2015, ), Wydawca: JMLR: Workshop and Conference Proceedings
    Data:
    konferencja 20-22/11/2015
    Status:
    Published
    DOI:
    link to the publication
  3. Extreme F-measure Maximization using Sparse Probability Estimates
    Authors:
    Kalina Jasinska, Krzysztof Dembczynski, Róbert Busa-Fekete, Karlson Pfannschmidt, Timo Klerx, Eyke Hüllermeier
    Conference:
    International Conference on Machine Learning (rok: 2016, ), Wydawca: Proceedings of Machine Learning Research
    Data:
    konferencja 20-22 czerwiec 2016
    Status:
    Published
    DOI:
    link to the publication
  1. Consistency of Probabilistic Classifier Trees
    Authors:
    Krzysztof Dembczynski, Wojciech Kotlowski, Willem Waegeman, Róbert Busa-Fekete, Eyke Hüllermeier
    Book:
    ECML PKDD 2016: Machine Learning and Knowledge Discovery in Databases (rok: 2016, tom: 9852, strony: 511-526), Wydawca: Springer
    Status:
    Published
    DOI:
    link to the publication

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