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Published in Artificial Intelligence and Machine Learning for Multi-Domain Operations Applications, 2019
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Recommended citation: Than, K., Bui, X., Nguyen-Trong, T., Truong, K., Nguyen, S., Tran, B., Van, L.N. and Nguyen-Duc, A., 2019, May. How to make a machine learn continuously: a tutorial of the Bayesian approach. In Artificial Intelligence and Machine Learning for Multi-Domain Operations Applications (Vol. 11006, p. 110060I). International Society for Optics and Photonics. https://www.spiedigitallibrary.org/conference-proceedings-of-spie/11006/110060I/How-to-make-a-machine-learn-continuously--a-tutorial/10.1117/12.2518860.short
Published in arXiv preprint arXiv:2003.06123, 2020
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Recommended citation: Bach, T. X., Anh, N. D., Van, L. N., & Than, K. (2020). Dynamic transformation of prior knowledge into Bayesian models for data streams. arXiv preprint arXiv:2003.06123. https://arxiv.org/pdf/2003.06123.pdf
Published in arXiv preprint arXiv:2003.06112, 2020
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Recommended citation: Van, L. N., Tran, B., & Than, K. (2020). Graph Convolutional Topic Model for Data Streams. arXiv preprint arXiv:2003.06112. https://arxiv.org/pdf/2003.06112.pdf
Published in Knowledge and Information Systems volume 62, pages4055–4090(2020), 2020
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Recommended citation: Tuan, A. P., Tran, B., Nguyen, T. H., Van, L. N., & Than, K. (2020). Bag of biterms modeling for short texts. Knowledge and Information Systems, 62(10), 4055-4090. https://link.springer.com/article/10.1007/s10115-020-01482-z
Published:
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Undergraduate course, University 1, Department, 2014
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Workshop, University 1, Department, 2015
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