Projects funded by the NCN
Efficient extreme classification algorithms based on reduction to structured prediction problems
2017/25/N/ST6/00747
Keywords:
machine learning extreme classification efficient machine learning algorithms
Descriptors:
- ST6_11: Machine learning, statistical data processing and applications using signal processing (e.g. speech, image, video)
Panel:
ST6 - Computer science and informatics: informatics and information systems, computer science, scientific computing, intelligent systems
Host institution :
Politechnika Poznańska, Wydział Informatyki
woj. wielkopolskie
Principal investigator (from the host institution):
Number of co-investigators in the project: 2
Call: PRELUDIUM 13 - announced on 2017-03-15
Amount awarded: 36 746 PLN
Project start date (Y-m-d): 2018-02-21
Project end date (Y-m-d): 2019-02-20
Project duration:: 12 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.
Information in the final report
- Publication in academic press/journals (1)
- Articles in post-conference publications (1)
- Probabilistic Label Trees for Extreme Multi-Label ClassificationAuthors:Kalina Kobus, Marek Wydmuch, Krzysztof Dembczyński, Mikhail Kuznetsov, Robert Busa-FeketeAcademic press:Journal of Machine Learning Research , Wydawca: jmlr.orgStatus:SubmittedDOI:brak - link to the publication
- A no-regret generalization of hierarchical softmax to extreme multi-label classificationAuthors:Marek Wydmuch, Kalina Jasinska, Mikhail Kuznetsov, Robert Busa-Fekete, Krzysztof DembczyńskiConference:Neural Information Processing Systems (rok: 2018, ), Wydawca: Curran Associates, Inc.Data:konferencja 2-8.12.2018Status:Published