Trong Nghia Hoang
Trong Nghia Hoang
Senior Machine Learning Scientist, Amazon
Adresse e-mail validée de amazon.com - Page d'accueil
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Bayesian nonparametric federated learning of neural networks
YK Mikhail Yurochkin, Mayank Agarwal, Soumya Ghosh, Kristjan Greenewald ...
International Conference on Machine Learning, 7252-7261, 2019
712019
A unifying framework of anytime sparse Gaussian process regression models with stochastic variational inference for big data
TN Hoang, QM Hoang, BKH Low
International Conference on Machine Learning, 569-578, 2015
632015
Nonmyopic ε-Bayes-optimal active learning of Gaussian processes
TN Hoang, BKH Low, P Jaillet, M Kankanhalli
International Conference on Machine Learning, 739-747, 2014
522014
A distributed variational inference framework for unifying parallel sparse Gaussian process regression models
TN Hoang, QM Hoang, BKH Low
International Conference on Machine Learning, 382-391, 2016
432016
Decision-theoretic approach to maximizing observation of multiple targets in multi-camera surveillance
P Natarajan, TN Hoang, KH Low, M Kankanhalli
Proceedings of the 11th International Conference on Autonomous Agents and …, 2012
412012
Decentralized High-Dimensional Bayesian Optimization with Factor Graphs
TN Hoang, QM Hoang, R Ouyang, KH Low
32nd AAAI Conference on Artificial Intelligence (AAAI-18), 2018
332018
A generalized stochastic variational Bayesian hyperparameter learning framework for sparse spectrum Gaussian process regression
QM Hoang, TN Hoang, KH Low
Proceedings of the AAAI Conference on Artificial Intelligence 31 (1), 2017
302017
Information-based multi-fidelity Bayesian optimization
Y Zhang, TN Hoang, BKH Low, M Kankanhalli
NIPS Workshop on Bayesian Optimization, 2017
292017
Near-optimal active learning of multi-output Gaussian processes
Y Zhang, TN Hoang, KH Low, M Kankanhalli
Proceedings of the AAAI Conference on Artificial Intelligence 30 (1), 2016
282016
Interactive POMDP Lite: Towards practical planning to predict and exploit intentions for interacting with self-interested agents
TN Hoang, KH Low
arXiv preprint arXiv:1304.5159, 2013
282013
On the design of black-box adversarial examples by leveraging gradient-free optimization and operator splitting method
P Zhao, S Liu, PY Chen, N Hoang, K Xu, B Kailkhura, X Lin
Proceedings of the IEEE/CVF International Conference on Computer Vision, 121-130, 2019
252019
Scalable decision-theoretic coordination and control for real-time active multi-camera surveillance
P Natarajan, TN Hoang, Y Wong, KH Low, M Kankanhalli
Proceedings of the International Conference on Distributed Smart Cameras, 1-6, 2014
252014
Collective online learning of Gaussian processes in massive multi-agent systems
TN Hoang, QM Hoang, KH Low, J How
Proceedings of the AAAI Conference on Artificial Intelligence 33 (01), 7850-7857, 2019
212019
Recent advances in scaling up Gaussian process predictive models for large spatiotemporal data
KH Low, J Chen, TN Hoang, N Xu, P Jaillet
International Conference on Dynamic Data-Driven Environmental Systems …, 2014
212014
Stochastic variational inference for Bayesian sparse Gaussian process regression
H Yu, T Nghia, BKH Low, P Jaillet
2019 International Joint Conference on Neural Networks (IJCNN), 1-8, 2019
152019
Collective Model Fusion for Multiple Black-Box Experts
CK Quang Minh Hoang, Trong Nghia Hoang, Bryan Kian Hsiang Low
International Conference on Machine Learning, 2742-2750, 2019
142019
Active Learning Is Planning: Nonmyopic ε-Bayes-Optimal Active Learning of Gaussian Processes
TN Hoang, KH Low, P Jaillet, M Kankanhalli
Joint European Conference on Machine Learning and Knowledge Discovery in …, 2014
132014
Caster: Predicting drug interactions with chemical substructure representation
K Huang, C Xiao, T Hoang, L Glass, J Sun
Proceedings of the AAAI Conference on Artificial Intelligence 34 (01), 702-709, 2020
122020
A general framework for interacting Bayes-optimally with self-interested agents using arbitrary parametric model and model prior
TN Hoang, KH Low
arXiv preprint arXiv:1304.2024, 2013
112013
DDL: Deep Dictionary Learning for Predictive Phenotyping.
T Fu, TN Hoang, C Xiao, J Sun
IJCAI, 5857-5863, 2019
72019
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