Log InRegister
Quick Links : The Mindat ManualThe Rock H. Currier Digital LibraryMindat Newsletter [Free Download]
Home PageAbout MindatThe Mindat ManualHistory of MindatCopyright StatusWho We AreContact UsAdvertise on Mindat
Donate to MindatCorporate SponsorshipSponsor a PageSponsored PagesMindat AdvertisersAdvertise on Mindat
Learning CenterWhat is a mineral?The most common minerals on earthInformation for EducatorsMindat ArticlesThe ElementsThe Rock H. Currier Digital LibraryGeologic Time
Minerals by PropertiesMinerals by ChemistryAdvanced Locality SearchRandom MineralRandom LocalitySearch by minIDLocalities Near MeSearch ArticlesSearch GlossaryMore Search Options
Search For:
Mineral Name:
Locality Name:
Keyword(s):
 
The Mindat ManualAdd a New PhotoRate PhotosLocality Edit ReportCoordinate Completion ReportAdd Glossary Item
Mining CompaniesStatisticsUsersMineral MuseumsClubs & OrganizationsMineral Shows & EventsThe Mindat DirectoryDevice SettingsThe Mineral Quiz
Photo SearchPhoto GalleriesSearch by ColorNew Photos TodayNew Photos YesterdayMembers' Photo GalleriesPast Photo of the Day GalleryPhotography

Cumani, Sandro, Laface, Pietro (2019) Exact memory–constrained UPGMA for large scale speaker clustering. Pattern Recognition, 95. 235-246 doi:10.1016/j.patcog.2019.06.018

Advanced
   -   Only viewable:
Reference TypeJournal (article/letter/editorial)
TitleExact memory–constrained UPGMA for large scale speaker clustering
JournalPattern Recognition
AuthorsCumani, SandroAuthor
Laface, PietroAuthor
Year2019 (November)Volume95
PublisherElsevier BV
DOIdoi:10.1016/j.patcog.2019.06.018Search in ResearchGate
Generate Citation Formats
Mindat Ref. ID9367907Long-form Identifiermindat:1:5:9367907:3
GUID0
Full ReferenceCumani, Sandro, Laface, Pietro (2019) Exact memory–constrained UPGMA for large scale speaker clustering. Pattern Recognition, 95. 235-246 doi:10.1016/j.patcog.2019.06.018
Plain TextCumani, Sandro, Laface, Pietro (2019) Exact memory–constrained UPGMA for large scale speaker clustering. Pattern Recognition, 95. 235-246 doi:10.1016/j.patcog.2019.06.018
In(2019) Pattern Recognition Vol. 95. Elsevier BV

See Also

These are possibly similar items as determined by title/reference text matching only.

Ye, Xulun, Zhao, Jieyu (2019) Multi-manifold clustering: A graph-constrained deep nonparametric method. Pattern Recognition, 93. 215-227 doi:10.1016/j.patcog.2019.04.029
Vargas Muñoz, Javier, Gonçalves, Marcos A., Dias, Zanoni, da S. Torres, Ricardo (2019) Hierarchical Clustering-Based Graphs for Large Scale Approximate Nearest Neighbor Search. Pattern Recognition, 96. 106970pp. doi:10.1016/j.patcog.2019.106970
Jung, Kyu-Hwan, Lee, Daewon, Lee, Jaewook (2010) Fast support-based clustering method for large-scale problems. Pattern Recognition, 43 (5). 1975-1983 doi:10.1016/j.patcog.2009.12.010
Li, Zeqian, He, Xinlu, Whitehill, Jacob (2023) Compositional clustering: Applications to multi-label object recognition and speaker identification. Pattern Recognition, 144. Elsevier BV. 109829 doi:10.1016/j.patcog.2023.109829
Li, Jie, Li, Chaoqian (2025) One-hot constrained symmetric nonnegative matrix factorization for image clustering. Pattern Recognition, 162. doi:10.1016/j.patcog.2025.111427
Gao, Chenhui, Chen, Wenzhi, Nie, Feiping, Yu, Weizhong, Wang, Zonghui (2024) Spectral clustering with linear embedding: A discrete clustering method for large-scale data. Pattern Recognition, 151. 110396 doi:10.1016/j.patcog.2024.110396
Kong, Zisen; Fu, Zhiqiang; Chang, Dongxia; Wang, Yiming; Zhao, Yao (2025) Dual-space Co-training for Large-scale Multi-view Clustering. Pattern Recognition, 168. doi:10.1016/j.patcog.2025.111844
Wang, Liang, Leckie, Christopher, Kotagiri, Ramamohanarao, Bezdek, James (2011) Approximate pairwise clustering for large data sets via sampling plus extension. Pattern Recognition, 44 (2). 222-235 doi:10.1016/j.patcog.2010.08.005
Chen, Yewang, Zhou, Lida, Bouguila, Nizar, Wang, Cheng, Chen, Yi, Du, Jixiang (2021) BLOCK-DBSCAN: Fast clustering for large scale data. Pattern Recognition, 109. 107624pp. doi:10.1016/j.patcog.2020.107624
Karmitsa, Napsu, Bagirov, Adil M., Taheri, Sona (2018) Clustering in large data sets with the limited memory bundle method. Pattern Recognition, 83. 245-259 doi:10.1016/j.patcog.2018.05.028
Yang, Zengbiao, Tan, Yihua, Yang, Tao (2024) Large-scale multi-view clustering via matrix factorization of consensus graph. Pattern Recognition, 155. 110716 doi:10.1016/j.patcog.2024.110716
 
and/or  
Mindat.org is an outreach project of the Hudson Institute of Mineralogy, a 501(c)(3) not-for-profit organization.
Copyright © mindat.org and the Hudson Institute of Mineralogy 1993-2025, except where stated. Most political location boundaries are © OpenStreetMap contributors. Mindat.org relies on the contributions of thousands of members and supporters. Founded in 2000 by Jolyon Ralph.
To cite: Ralph, J., Von Bargen, D., Martynov, P., Zhang, J., Que, X., Prabhu, A., Morrison, S. M., Li, W., Chen, W., & Ma, X. (2025). Mindat.org: The open access mineralogy database to accelerate data-intensive geoscience research. American Mineralogist, 110(6), 833–844. doi:10.2138/am-2024-9486.
Privacy Policy - Terms & Conditions - Contact Us / DMCA issues - Report a bug/vulnerability Current server date and time: August 28, 2025 15:14:47
Go to top of page