20132019
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Network Recent external collaboration on country level. Dive into details by clicking on the dots.

Research Output 2013 2019

GoGP: scalable geometric-based Gaussian process for online regression

Le, T., Nguyen, K., Nguyen, V., Nguyen, T. D. & Phung, D., 20 Jul 2019, In : Knowledge and Information Systems. p. 197-226 30 p.

Research output: Contribution to journalArticleResearchpeer-review

Sqn2Vec: learning sequence representation via sequential patterns with a gap constraint

Nguyen, D., Luo, W., Nguyen, T. D., Venkatesh, S. & Phung, D., 2019, Machine Learning and Knowledge Discovery in Databases: European Conference, ECML PKDD 2018 Dublin, Ireland, September 10–14, 2018 Proceedings, Part II. Berlingerio, M., Bonchi, F., Gärtner, T., Hurley, N. & Ifrim, G. (eds.). Cham Switzerland: Springer, p. 569-584 16 p. (Lecture Notes in Computer Science ; vol. 11052 ).

Research output: Chapter in Book/Report/Conference proceedingConference PaperResearchpeer-review

A convolutional neural network-based model for knowledge base completion and its application to search personalization

Nguyen, D. Q., Nguyen, D. Q., Nguyen, T. D. & Phung, D., 2018, In : Semantic Web. 14 p.

Research output: Contribution to journalArticleResearchpeer-review

Open Access
File

A novel embedding model for knowledge base completion based on convolutional neural network

Quoc Nguyen, D., Nguyen, T. D., Nguyen, D. Q. & Phung, D., 2018, The 2018 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Proceedings of the Conference Volume 2 (Short Papers). Ji, H. & Stent, A. (eds.). Stroudsburg PA USA: Association for Computational Linguistics (ACL), p. 327–333 7 p.

Research output: Chapter in Book/Report/Conference proceedingConference PaperResearchpeer-review

Open Access
File

Batch Normalized Deep Boltzmann Machines

Vu, H., Nguyen, T. D., Le, T., Luo, W. & Phung, D., 2018, Proceedings of Asian Conference on Machine Learning 2018. Zhu, J. & Takeuchi, I. (eds.). USA: Proceedings of Machine Learning Research (PMLR), p. 359-374 16 p. (Proceedings of Machine Learning Research; vol. 95).

Research output: Chapter in Book/Report/Conference proceedingConference PaperResearchpeer-review

Open Access
File