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Combination of Active Learning and Semi-Supervised Learning under a Self-Training Scheme.

, , , , и . Entropy, 21 (10): 988 (2019)

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Blagoje Nikosavi

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Optimized Active Learning Strategy for Audiovisual Speaker Recognition., , , , и . SPECOM, том 11096 из Lecture Notes in Computer Science, стр. 281-290. Springer, (2018)An incremental self-trained ensemble algorithm., , , , и . EAIS, стр. 1-8. IEEE, (2018)Effectiveness of semi-supervised learning in bankruptcy prediction., , , и . IISA, стр. 1-6. IEEE, (2016)A multi-scheme semi-supervised regression approach., , , и . Pattern Recognit. Lett., (2019)Speech Recognition Combining MFCCs and Image Features., , , , и . SPECOM, том 9811 из Lecture Notes in Computer Science, стр. 651-658. Springer, (2016)A Semi-supervised regressor based on model trees., , , и . SETN, стр. 6:1-6:7. ACM, (2018)Semi-supervised forecasting of fraudulent financial statements., , , и . PCI, стр. 34. ACM, (2016)Optimal Team Pairing of Elder Office Employees with Machine Learning on Synthetic Data., , , , и . IISA, стр. 1-4. IEEE, (2021)Investigating the Benefits of Exploiting Incremental Learners Under Active Learning Scheme., , , , и . AIAI, том 559 из IFIP Advances in Information and Communication Technology, стр. 37-49. Springer, (2019)An active learning ensemble method for regression tasks., , , , и . Intell. Data Anal., 24 (3): 607-623 (2020)