6 citations · 18 across the 11 of their papers we have counts for
11 papers
PrivImage: Differentially Private Synthetic Image Generation using Diffusion Models with Semantic-Aware Pretraining
Kecen Li, Chen Gong, Zhixiang Li +3
Differential Privacy (DP) image data synthesis, which leverages the DP technique to generate synthetic data to replace the sensitive data, allowing organizations to share and utili…
Keep Various Trajectories: Promoting Exploration of Ensemble Policies in Continuous Control
Chao Li, Chen Gong, Qiang He +1
The combination of deep reinforcement learning (DRL) with ensemble methods has been proved to be highly effective in addressing complex sequential decision-making problems. This su…
A Hierarchical Approach to Population Training for Human-AI Collaboration
Yi Loo, Chen Gong, Malika Meghjani
A major challenge for deep reinforcement learning (DRL) agents is to collaborate with novel partners that were not encountered by them during the training phase. This is specifical…
Recover Triggered States: Protect Model Against Backdoor Attack in Reinforcement Learning
Hao Chen, Chen Gong, Yizhe Wang +1
A backdoor attack allows a malicious user to manipulate the environment or corrupt the training data, thus inserting a backdoor into the trained agent. Such attacks compromise the…
Centralized Cooperative Exploration Policy for Continuous Control Tasks
Chao Li, Chen Gong, Qiang He +2
The deep reinforcement learning (DRL) algorithm works brilliantly on solving various complex control tasks. This phenomenal success can be partly attributed to DRL encouraging inte…
GAN Inversion for Image Editing via Unsupervised Domain Adaptation
Siyu Xing, Chen Gong, Hewei Guo +3
Existing GAN inversion methods work brilliantly in reconstructing high-quality (HQ) images while struggling with more common low-quality (LQ) inputs in practical application. To ad…
BAFFLE: Hiding Backdoors in Offline Reinforcement Learning Datasets
Chen Gong, Zhou Yang, Yunpeng Bai +8
Reinforcement learning (RL) makes an agent learn from trial-and-error experiences gathered during the interaction with the environment. Recently, offline RL has become a popular RL…
Cooperative Multi-Agent Reinforcement Learning with Hypergraph Convolution
Yunpeng Bai, Chen Gong, Bin Zhang +3
Recent years have witnessed the great success of multi-agent systems (MAS). Value decomposition, which decomposes joint action values into individual action values, has been an imp…
The -Divergence Reinforcement Learning Framework
Chen Gong, Qiang He, Yunpeng Bai +6
The framework of deep reinforcement learning (DRL) provides a powerful and widely applicable mathematical formalization for sequential decision-making. This paper present a novel D…
LDC-VAE: A Latent Distribution Consistency Approach to Variational AutoEncoders
Xiaoyu Chen, Chen Gong, Qiang He +2
Variational autoencoders (VAEs), as an important aspect of generative models, have received a lot of research interests and reached many successful applications. However, it is alw…
MEPG: A Minimalist Ensemble Policy Gradient Framework for Deep Reinforcement Learning
Qiang He, Huangyuan Su, Chen Gong +1
During the training of a reinforcement learning (RL) agent, the distribution of training data is non-stationary as the agent's behavior changes over time. Therefore, there is a ris…