Personal profile
Author IDs
ORCID iD: 0000-0001-9245-6248
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Dive into the research topics where Lei YU is active. These topic labels come from the works of this person. Together they form a unique fingerprint.
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Collaborations from the last five years
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Research output
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PRIMAL-GMM: PaRametrIc MAnifold Learning of Gaussian Mixture Models
Liu, Z., Yu, L., Hsiao, J. H. & Chan, A. B., Jun 2022, In: IEEE Transactions on Pattern Analysis and Machine Intelligence. 44, 6, p. 3197-3211Research output: Journal Publications and Reviews › RGC 21 - Publication in refereed journal › peer-review
Open AccessFile7 Link opens in a new tab Citations (Scopus)47 Downloads (CityUHK Scholars) -
Density-Preserving Hierarchical EM Algorithm: Simplifying Gaussian Mixture Models for Approximate Inference
Yu, L., Yang, T. & Chan, A. B., Jun 2019, In: IEEE Transactions on Pattern Analysis and Machine Intelligence. 41, 6, p. 1323-1337Research output: Journal Publications and Reviews › RGC 21 - Publication in refereed journal › peer-review
Open AccessFile36 Link opens in a new tab Citations (Scopus)93 Downloads (CityUHK Scholars) -
Parametric Manifold Learning of Gaussian Mixture Models
Liu, Z., Yu, L., Hsiao, J. H. & Chan, A. B., Aug 2019, Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence (IJCAI-19). Kraus, S. (ed.). Macau: International Joint Conferences on Artificial Intelligence, p. 3073-3079 (IJCAI International Joint Conference on Artificial Intelligence; vol. 2019-August).Research output: Chapters, Conference Papers, Creative and Literary Works › RGC 32 - Refereed conference paper (with host publication) › peer-review
Open Access2 Link opens in a new tab Citations (Scopus) -
Approximate Inference for Generic Likelihoods via Density-Preserving GMM Simplification
YU, L., YANG, T. & Chan, A. B., Dec 2016.Research output: Conference Papers › RGC 32 - Refereed conference paper (without host publication) › peer-review
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Small Instance Detection by Integer Programming on Object Density Maps
MA, Z., YU, L. & CHAN, A. B., 8 Jun 2015.Research output: Conference Papers › RGC 32 - Refereed conference paper (without host publication) › peer-review
65 Link opens in a new tab Citations (Scopus)
Thesis
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Approximate Inference Using Simplification of Gaussian Mixture Models
YU, L. (Author), CHAN, A. B. (Supervisor), 11 Dec 2018Student thesis: Doctoral Thesis