7 citations · 21 across the 12 of their papers we have counts for
12 papers
Co-evolution of social reward and punishment under institutional interventions
Van An Nguyen, Vuong Khang Huynh, Hoai Thuong Nguyen +14
We investigate how peer and institutional incentives jointly shape the evolution of cooperation, social welfare, and enforcement efficiency in social dilemmas. In a Prisoners Dilem…
Hierarchical Molecular Representation Learning via Fragment-Based Self-Supervised Embedding Prediction
Jiele Wu, Haozhe Ma, Zhihan Guo +2
Graph self-supervised learning (GSSL) has demonstrated strong potential for generating expressive graph embeddings without the need for human annotations, making it particularly va…
Causal Policy Learning in Reinforcement Learning: Backdoor-Adjusted Soft Actor-Critic
Thanh Vinh Vo, Young Lee, Haozhe Ma +2
Hidden confounders that influence both states and actions can bias policy learning in reinforcement learning (RL), leading to suboptimal or non-generalizable behavior. Most RL algo…
Centralized Reward Agent for Knowledge Sharing and Transfer in Multi-Task Reinforcement Learning
Haozhe Ma, Zhengding Luo, Thanh Vinh Vo +2
Reward shaping is effective in addressing the sparse-reward challenge in reinforcement learning (RL) by providing immediate feedback through auxiliary, informative rewards. Based o…
Highly Efficient Self-Adaptive Reward Shaping for Reinforcement Learning
Haozhe Ma, Zhengding Luo, Thanh Vinh Vo +2
Reward shaping is a technique in reinforcement learning that addresses the sparse-reward problem by providing more frequent and informative rewards. We introduce a self-adaptive an…
Decoupled Prompt-Adapter Tuning for Continual Activity Recognition
Di Fu, Thanh Vinh Vo, Haozhe Ma +1
Action recognition technology plays a vital role in enhancing security through surveillance systems, enabling better patient monitoring in healthcare, providing in-depth performanc…
Federated Causal Inference from Observational Data
Thanh Vinh Vo, Young lee, Tze-Yun Leong
Decentralized data sources are prevalent in real-world applications, posing a formidable challenge for causal inference. These sources cannot be consolidated into a single entity o…
An Adaptive Kernel Approach to Federated Learning of Heterogeneous Causal Effects
Thanh Vinh Vo, Arnab Bhattacharyya, Young Lee +1
We propose a new causal inference framework to learn causal effects from multiple, decentralized data sources in a federated setting. We introduce an adaptive transfer algorithm th…
Federated Estimation of Causal Effects from Observational Data
Thanh Vinh Vo, Trong Nghia Hoang, Young Lee +1
Many modern applications collect data that comes in federated spirit, with data kept locally and undisclosed. Till date, most insight into the causal inference requires data to be…
Adaptive Multi-Source Causal Inference
Thanh Vinh Vo, Pengfei Wei, Trong Nghia Hoang +1
Data scarcity is a tremendous challenge in causal effect estimation. In this paper, we propose to exploit additional data sources to facilitate estimating causal effects in the tar…
Causal Modeling with Stochastic Confounders
Thanh Vinh Vo, Pengfei Wei, Wicher Bergsma +1
This work extends causal inference with stochastic confounders. We propose a new approach to variational estimation for causal inference based on a representer theorem with a rando…
Generation Meets Recommendation: Proposing Novel Items for Groups of Users
Vinh Vo Thanh, Harold Soh
Consider a movie studio aiming to produce a set of new movies for summer release: What types of movies it should produce? Who would the movies appeal to? How many movies should it…