Author of the publication

copy delete add this publication to your clipboard
community post
history of this post
URL
DOI
BibTeX
EndNote
APA
Chicago
DIN 1505
Harvard
MSOffice XML

Pre-trained Recommender Systems: A Causal Debiasing Perspective.

Z. Lin, H. Ding, N. Hoang, B. Kveton, A. Deoras, and H. Wang. CoRR, (2023)

Please choose a person to relate this publication to

To differ between persons with the same name, the academic degree and the title of an important publication will be displayed. You can also use the button next to the name to display some publications already assigned to the person.

Hoang-Duc-Nghia

Tang-Van Nghia

Duc-Dang Nghia

Nguyen Nghia Binh

Pham Duy Nghia

Other publications of authors with the same name

On the Design of Black-Box Adversarial Examples by Leveraging Gradient-Free Optimization and Operator Splitting Method.P. Zhao, S. Liu, P. Chen, N. Hoang, K. Xu, B. Kailkhura, and X. Lin. ICCV, page 121-130. IEEE, (2019)Revisiting the Sample Complexity of Sparse Spectrum Approximation of Gaussian Processes.Q. Hoang, N. Hoang, H. Pham, and D. Woodruff. NeurIPS, (2020)Pre-trained Recommender Systems: A Causal Debiasing Perspective.Z. Lin, H. Ding, N. Hoang, B. Kveton, A. Deoras, and H. Wang. CoRR, (2023)Federated Estimation of Causal Effects from Observational Data.T. Vo, T. Hoang, Y. Lee, and T. Leong. CoRR, (2021)Nonmyopic \(\epsilon\)-Bayes-Optimal Active Learning of Gaussian Processes.T. Hoang, B. Low, P. Jaillet, and M. Kankanhalli. ICML, volume 32 of JMLR Workshop and Conference Proceedings, page 739-747. JMLR.org, (2014)A Unifying Framework of Anytime Sparse Gaussian Process Regression Models with Stochastic Variational Inference for Big Data.T. Hoang, Q. Hoang, and B. Low. ICML, volume 37 of JMLR Workshop and Conference Proceedings, page 569-578. JMLR.org, (2015)Collective Model Fusion for Multiple Black-Box Experts.Q. Hoang, T. Hoang, B. Low, and C. Kingsford. ICML, volume 97 of Proceedings of Machine Learning Research, page 2742-2750. PMLR, (2019)Stochastic Variational Inference for Bayesian Sparse Gaussian Process Regression.H. Yu, T. Hoang, B. Low, and P. Jaillet. IJCNN, page 1-8. IEEE, (2019)Bayesian federated estimation of causal effects from observational data.T. Vo, Y. Lee, T. Hoang, and T. Leong. UAI, volume 180 of Proceedings of Machine Learning Research, page 2024-2034. PMLR, (2022)Near-Optimal Active Learning of Multi-Output Gaussian Processes.Y. Zhang, T. Hoang, K. Low, and M. Kankanhalli. AAAI, page 2351-2357. AAAI Press, (2016)

BibSonomy

Disambiguation of "Hoang, Nghia"

copy delete add this publication to your clipboard
community post
history of this post
URL
DOI
BibTeX
EndNote
APA
Chicago
DIN 1505
Harvard
MSOffice XML

Pre-trained Recommender Systems: A Causal Debiasing Perspective.

Please choose a person to relate this publication to

Hoang-Duc-Nghia

Tang-Van Nghia

Duc-Dang Nghia

Nguyen Nghia Binh

Pham Duy Nghia

Other publications of authors with the same name

Disambiguation

BibSonomy

Disambiguation of "Hoang, Nghia"

copydeleteadd this publication to your clipboardcommunity posthistory of this postURLDOIBibTeXEndNoteAPAChicagoDIN 1505HarvardMSOffice XML Pre-trained Recommender Systems: A Causal Debiasing Perspective.

Please choose a person to relate this publication to

Hoang-Duc-Nghia

Tang-Van Nghia

Duc-Dang Nghia

Nguyen Nghia Binh

Pham Duy Nghia

Other publications of authors with the same name

Disambiguation

copy delete add this publication to your clipboard
community post
history of this post
URL
DOI
BibTeX
EndNote
APA
Chicago
DIN 1505
Harvard
MSOffice XML

Pre-trained Recommender Systems: A Causal Debiasing Perspective.