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Found 110 Documents (Results 1–100)

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Multi-label learning with a cone-based geometric model. (English) Zbl 1476.68233

Alam, Mehwish (ed.) et al., Ontologies and concepts in mind and machine. 25th international conference on conceptual structures, ICCS 2020, Bolzano, Italy, September 18–20, 2020. Proceedings. Cham: Springer. Lect. Notes Comput. Sci. 12277, 177-185 (2020).
MSC:  68T05 68T30
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Rule-based multi-label classification: challenges and opportunities. (English) Zbl 1478.68289

Gutiérrez-Basulto, Víctor (ed.) et al., Rules and reasoning. 4th international joint conference, RuleML+RR 2020, Oslo, Norway, June 29 – July 1, 2020. Proceedings. Cham: Springer. Lect. Notes Comput. Sci. 12173, 3-19 (2020).
MSC:  68T05 62H30
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Multi-label learning through minimum spanning tree-based subset selection and feature extraction. (English) Zbl 1454.68130

Mouhoub, Malek (ed.) et al., Advances in artificial intelligence. 30th Canadian conference on artificial intelligence, Canadian AI 2017, Edmonton, AB, Canada, May 16–19, 2017. Proceedings. Cham: Springer. Lect. Notes Comput. Sci. 10233, 90-96 (2017).
MSC:  68T05 62H30
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Secure multi-label classification over encrypted data in cloud. (English) Zbl 1439.94045

Okamoto, Tatsuaki (ed.) et al., Provable security. 11th international conference, ProvSec 2017, Xi’an, China, October 23–25, 2017. Proceedings. Cham: Springer. Lect. Notes Comput. Sci. 10005, 57-73 (2017).
MSC:  94A60 68P25
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Sparse matrix feature selection in multi-label learning. (English) Zbl 1444.68165

Yao, Yiyu (ed.) et al., Rough sets, fuzzy sets, data mining, and granular computing. 15th international conference, RSFDGrC 2015, Tianjin, China, November 20–23, 2015. Proceedings. Cham: Springer. Lect. Notes Comput. Sci. 9437, 332-339 (2015).
MSC:  68T05
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Generalizing labeled and unlabeled sample compression to multi-label concept classes. (English) Zbl 1432.68398

Auer, Peter (ed.) et al., Algorithmic learning theory. 25th international conference, ALT 2014, Bled, Slovenia, October 8–10, 2014. Proceedings. Berlin: Springer. Lect. Notes Comput. Sci. 8776, 275-290 (2014).
MSC:  68T05 68P30
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Expressive power of binary relevance and chain classifiers based on Bayesian networks for multi-label classification. (English) Zbl 1443.62189

van der Gaag, Linda C. (ed.) et al., Probabilistic graphical models. 7th European workshop, PGM 2014, Utrecht, The Netherlands, September 17–19, 2014. Proceedings. Berlin: Springer. Lect. Notes Comput. Sci. 8754, 519-534 (2014).
MSC:  62H30 62H22 68T05
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Predicting gene function using predictive clustering trees. (English) Zbl 1211.68172

Džeroski, Sašo (ed.) et al., Inductive databases and constraint-based data mining. New York, NY: Springer (ISBN 978-1-4419-7737-3/hbk; 978-1-4419-7738-0/ebook). 365-387 (2010).
MSC:  68P15 68T10 68T05
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Dempster-Shafer reasoning in large partially ordered sets: applications in machine learning. (English) Zbl 1215.68228

Huynh, Van-Nam (ed.) et al., Integrated uncertainty management and applications. Selected papers based on the presentations at the 2010 international symposium on integrated uncertainty managment and applications (IUM 2010), Ishikawa, Japan, April 9–11, 2010. Berlin: Springer (ISBN 978-3-642-11959-0/pbk; 978-3-642-11960-6/ebook). Advances in Intelligent and Soft Computing 68, 39-54 (2010).
MSC:  68T37 68T05
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