0533916 - ÚI 2021 RIV DE eng C - Conference Paper (international conference)
Dědič, M. - Pevný, T. - Bajer, L. - Holeňa, MartinLoss Functions for Clustering in Multi-instance Learning.
Proceedings of the 20th Conference Information Technologies - Applications and Theory. Aachen: Technical University & CreateSpace Independent Publishing, 2020 - (Holeňa, M.; Horváth, T.; Kelemenová, A.; Mráz, F.; Pardubská, D.; Plátek, M.; Sosík, P.), s. 137-146. CEUR Workshop Proceedings, 2718. ISSN 1613-0073.
[ITAT 2020: Information Technologies - Applications and Theory /20./. Oravská Lesná (SK), 18.09.2020-22.09.2020]
R&D Projects: GA ČR(CZ) GA18-18080S
Grant - others:GA ČR(CZ) GA18-21409S
Program: GA
Institutional support: RVO:67985807
Keywords : Representation learning * Multi-instance learning * Multi-instance clustering * Clustering loss functions * Intrusion detection
OECD category: Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
http://ceur-ws.org/Vol-2718/paper05.pdf
Permanent Link: http://hdl.handle.net/11104/0312145