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ORCIDThanh Vinh Vo
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2020 – today
- 2024
[c10]Haozhe Ma, Thanh Vinh Vo, Tze-Yun Leong:
Mixed-Initiative Bayesian Sub-Goal Optimization in Hierarchical Reinforcement Learning. AAMAS 2024: 1328-1336- [c9]Haozhe Ma, Kuankuan Sima, Thanh Vinh Vo, Di Fu, Tze-Yun Leong:
Reward Shaping for Reinforcement Learning with An Assistant Reward Agent. ICML 2024 - [i9]Di Fu, Thanh Vinh Vo, Haozhe Ma, Tze-Yun Leong:
Decoupled Prompt-Adapter Tuning for Continual Activity Recognition. CoRR abs/2407.14811 (2024) - [i8]Haozhe Ma, Zhengding Luo, Thanh Vinh Vo, Kuankuan Sima, Tze-Yun Leong:
Highly Efficient Self-Adaptive Reward Shaping for Reinforcement Learning. CoRR abs/2408.03029 (2024) - [i7]Haozhe Ma, Zhengding Luo, Thanh Vinh Vo, Kuankuan Sima, Tze-Yun Leong:
Knowledge Sharing and Transfer via Centralized Reward Agent for Multi-Task Reinforcement Learning. CoRR abs/2408.10858 (2024) - 2023
- [j1]Pengfei Wei
, Thanh Vinh Vo, Xinghua Qu, Yew Soon Ong, Zejun Ma:
Transfer Kernel Learning for Multi-Source Transfer Gaussian Process Regression. IEEE Trans. Pattern Anal. Mach. Intell. 45(3): 3862-3876 (2023) - [c8]Haozhe Ma, Thanh Vinh Vo, Tze-Yun Leong:
Hierarchical Reinforcement Learning with Human-AI Collaborative Sub-Goals Optimization. AAMAS 2023: 2310-2312 - [c7]Evangelos Sigalas, Thanh Vinh Vo, Tze-Yun Leong, Camilo Libedinsky:
Discovering Low-Dimensional Causal Pathways between Multiple Interacting Neuronal Populations. CogSci 2023 - [i6]Thanh Vinh Vo, Arnab Bhattacharyya, Young Lee, Tze-Yun Leong:
An Adaptive Kernel Approach to Federated Learning of Heterogeneous Causal Effects. CoRR abs/2301.00346 (2023) - [i5]Thanh Vinh Vo, Young Lee, Tze-Yun Leong:
Federated Learning of Causal Effects from Incomplete Observational Data. CoRR abs/2308.13047 (2023) - 2022
- [c6]Thanh Vinh Vo, Pengfei Wei, Trong Nghia Hoang, Tze-Yun Leong:
Adaptive Multi-Source Causal Inference from Observational Data. CIKM 2022: 1975-1985 - [c5]Thanh Vinh Vo, Arnab Bhattacharyya, Young Lee, Tze-Yun Leong:
An Adaptive Kernel Approach to Federated Learning of Heterogeneous Causal Effects. NeurIPS 2022 - [c4]Thanh Vinh Vo, Young Lee, Trong Nghia Hoang, Tze-Yun Leong:
Bayesian federated estimation of causal effects from observational data. UAI 2022: 2024-2034 - 2021
- [c3]Thanh Vinh Vo, Pengfei Wei, Wicher Bergsma, Tze-Yun Leong:
Causal Modeling with Stochastic Confounders. AISTATS 2021: 3025-3033 - [i4]Thanh Vinh Vo, Pengfei Wei, Trong Nghia Hoang, Tze-Yun Leong:
Adaptive Multi-Source Causal Inference. CoRR abs/2105.14877 (2021) - [i3]Thanh Vinh Vo, Trong Nghia Hoang, Young Lee, Tze-Yun Leong:
Federated Estimation of Causal Effects from Observational Data. CoRR abs/2106.00456 (2021) - 2020
- [i2]Thanh Vinh Vo, Pengfei Wei, Wicher Bergsma, Tze-Yun Leong:
A Causal Modeling Framework with Stochastic Confounders. CoRR abs/2004.11497 (2020)
2010 – 2019
- 2018
- [c2]Young Lee, Thanh Vinh Vo, Kar Wai Lim, Harold Soh:
Z-Transforms and its Inference on Partially Observable Point Processes. IJCAI 2018: 2369-2375 - [c1]Thanh Vinh Vo, Harold Soh:
Generation meets recommendation: proposing novel items for groups of users. RecSys 2018: 145-153 - [i1]Thanh Vinh Vo, Harold Soh:
Generation Meets Recommendation: Proposing Novel Items for Groups of Users. CoRR abs/1808.01199 (2018)
Coauthor Index
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