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2020 – today
- 2023
[j4]Dat Phan-Trong
, Hung Tran-The, Sunil Gupta:
NeuralBO: A black-box optimization algorithm using deep neural networks. Neurocomputing 559: 126776 (2023)- [c18]Tan M. Nguyen, Tam Nguyen, Long Bui, Hai Do, Duy Khuong Nguyen, Dung D. Le, Hung Tran-The, Nhat Ho, Stanley J. Osher, Richard G. Baraniuk:
A Probabilistic Framework for Pruning Transformers Via a Finite Admixture of Keys. ICASSP 2023: 1-5 - [c17]Hien Dang, Tho Tran Huu, Stanley J. Osher, Hung Tran-The, Nhat Ho, Tan Minh Nguyen:
Neural Collapse in Deep Linear Networks: From Balanced to Imbalanced Data. ICML 2023: 6873-6947 - [i9]Hien Dang, Tho Tran, Tan M. Nguyen, Stanley J. Osher, Hung Tran-The, Nhat Ho:
Neural Collapse in Deep Linear Networks: From Balanced to Imbalanced Data. CoRR abs/2301.00437 (2023) - [i8]Dat Phan-Trong, Hung Tran-The, Sunil Gupta:
Neural-BO: A Black-box Optimization Algorithm using Deep Neural Networks. CoRR abs/2303.01682 (2023) - 2022
- [j3]Thanh Nguyen-Tang, Sunil Gupta, Hung Tran-The, Svetha Venkatesh:
On Sample Complexity of Offline Reinforcement Learning with Deep ReLU Networks in Besov Spaces. Trans. Mach. Learn. Res. 2022 (2022) - [c16]Hung Tran-The, Sunil Gupta, Santu Rana, Svetha Venkatesh:
Regret Bounds for Expected Improvement Algorithms in Gaussian Process Bandit Optimization. AISTATS 2022: 8715-8737 - [c15]Hung Tran-The, Sunil Gupta, Santu Rana, Tuan Truong, Long Tran-Thanh, Svetha Venkatesh:
Expected Improvement for Contextual Bandits. NeurIPS 2022 - [i7]Hung Tran-The, Sunil Gupta, Santu Rana, Svetha Venkatesh:
Regret Bounds for Expected Improvement Algorithms in Gaussian Process Bandit Optimization. CoRR abs/2203.07875 (2022) - 2021
- [c14]Hung Tran-The, Sunil Gupta, Santu Rana, Svetha Venkatesh:
Bayesian Optimistic Optimisation with Exponentially Decaying Regret. ICML 2021: 10390-10400 - [i6]Thanh Nguyen-Tang, Sunil Gupta, Hung Tran-The, Svetha Venkatesh:
On Finite-Sample Analysis of Offline Reinforcement Learning with Deep ReLU Networks. CoRR abs/2103.06671 (2021) - [i5]Hung Tran-The, Sunil Gupta, Santu Rana, Svetha Venkatesh:
Bayesian Optimistic Optimisation with Exponentially Decaying Regret. CoRR abs/2105.04332 (2021) - [i4]Hung Tran-The, Sunil Gupta, Thanh Nguyen-Tang, Santu Rana, Svetha Venkatesh:
Combining Online Learning and Offline Learning for Contextual Bandits with Deficient Support. CoRR abs/2107.11533 (2021) - 2020
- [c13]Hung Tran-The, Sunil Gupta, Santu Rana, Svetha Venkatesh:
Trading Convergence Rate with Computational Budget in High Dimensional Bayesian Optimization. AAAI 2020: 2425-2432 - [c12]Hung Tran-The, Sunil Gupta, Santu Rana, Huong Ha, Svetha Venkatesh:
Sub-linear Regret Bounds for Bayesian Optimisation in Unknown Search Spaces. NeurIPS 2020 - [i3]Hung Tran-The, Sunil Gupta, Santu Rana, Huong Ha, Svetha Venkatesh:
Sub-linear Regret Bounds for Bayesian Optimisation in Unknown Search Spaces. CoRR abs/2009.02539 (2020)
2010 – 2019
- 2019
- [c11]Huong Ha, Santu Rana, Sunil Gupta, Thanh Tang Nguyen, Hung Tran-The, Svetha Venkatesh:
Bayesian Optimization with Unknown Search Space. NeurIPS 2019: 11772-11781 - [i2]Huong Ha, Santu Rana, Sunil Gupta, Thanh Tang Nguyen, Hung Tran-The, Svetha Venkatesh:
Bayesian Optimization with Unknown Search Space. CoRR abs/1910.13092 (2019) - [i1]Hung Tran-The, Sunil Gupta, Santu Rana, Svetha Venkatesh:
Trading Convergence Rate with Computational Budget in High Dimensional Bayesian Optimization. CoRR abs/1911.11950 (2019) - 2018
- [c10]Minh-Son Dao, Duc-Tien Dang-Nguyen, Asem Kasem, Hung Tran-The:
HealthyClassroom - A Proof-of-Concept Study for Discovering Students' Daily Moods and Classroom Emotions to Enhance a Learning-teaching Process using Heterogeneous Sensors. ICPRAM 2018: 685-691 - 2017
- [c9]Hung Tran-The, Koji Zettsu:
Discovering co-occurrence patterns of heterogeneous events from unevenly-distributed spatiotemporal data. IEEE BigData 2017: 1006-1011 - [c8]Hung Tran-The, Koji Zettsu:
Finding Spatiotemporal Co-occurrence Patterns of Heterogeneous Events for Prediction. EM-GIS 2017: 9:1-9:8 - 2015
- [c7]Hung Tran-The, Vinh Nguyen Van, Minh Hoang Anh:
Fast Approximate near Neighbor Algorithm by Clustering in High Dimensions. KSE 2015: 274-279 - 2014
- [c6]Carole Delporte-Gallet, Hugues Fauconnier, Hung Tran-The:
Leader Election in Rings with Homonyms. NETYS 2014: 9-24 - [c5]Hung Tran-The, Luís E. T. Rodrigues:
Tight Bounds for Stabilizing Uniform Consensus in Mobile Networks. SSS 2014: 328-342 - 2013
- [b1]Hung Tran-The:
Problème du Consensus dans le Modèle Homonyme. (The consensus problem in Homonymous models). Paris Diderot University, France, 2013 - [j2]Carole Delporte-Gallet, Hugues Fauconnier, Rachid Guerraoui, Anne-Marie Kermarrec, Eric Ruppert, Hung Tran-The:
Byzantine agreement with homonyms. Distributed Comput. 26(5-6): 321-340 (2013) - [j1]Carole Delporte-Gallet, Hugues Fauconnier, Hung Tran-The:
Byzantine agreement with homonyms in synchronous systems. Theor. Comput. Sci. 496: 34-49 (2013) - [c4]Carole Delporte-Gallet, Hugues Fauconnier, Hung Tran-The:
Uniform Consensus with Homonyms and Omission Failures. ICDCN 2013: 161-175 - 2012
- [c3]Carole Delporte-Gallet, Hugues Fauconnier, Hung Tran-The:
Byzantine Agreement with Homonyms in Synchronous Systems. ICDCN 2012: 76-90 - [c2]Carole Delporte-Gallet, Hugues Fauconnier, Hung Tran-The:
Homonyms with Forgeable Identifiers. SIROCCO 2012: 171-182 - 2011
- [c1]Carole Delporte-Gallet, Hugues Fauconnier, Rachid Guerraoui, Anne-Marie Kermarrec, Eric Ruppert, Hung Tran-The:
Byzantine agreement with homonyms. PODC 2011: 21-30
Coauthor Index
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