Ning Li

OrderMoE: An expert similarity driven distributed edge MoE inference

Xin Yuan, Ning Li, Quan Chen, Wenchao Xu, Athanasios V. Vasilakos, Song Guo, et al.

Although mixture-of-experts, MoE, models have been increasingly adopted to scale large language models with moderate computation cost, it remains challenging to deploy MoE inference over resource-constrained and bandwidth-limited edge infrastructures. Existing distributed MoE ser…Read more

Hierarchical Anti-Aesthetics: Protecting Facial Privacy against Customized Diffusion Models

Songping Wang, Yueming Lyu, Shiqi Liu, Chen Zhao, Ziyuan Chen, Ning Li, et al.

The rise of customized diffusion models has fueled a boom in personalized visual content creation, but it also introduces serious risks of malicious misuse, thereby posing threats to personal privacy. Image aesthetics are strongly correlated with human perception of image quality…Read more

Dynamic Scheduling for Flexible Manufacturing Systems Based on Multi-Agent Deep Reinforcement Learning and Petri Nets

Zhou He, Ning Li, Ruotian Liu, Liang Li, Carla Seatzu

This paper investigates dynamic scheduling for flexible manufacturing systems (FMSs) subject to dynamic events, such as new order arrivals, temporary order cancellations, and machine failures. Traditional methods often face significant challenges in achieving real-time responsive…Read more

Incremental Online Learning of Randomized Neural Network With Forward Regularization

Junda Wang, Minghui Hu, Ning Li, Abdulaziz Al-Ali, Ponnuthurai Nagaratnam Suganthan

Research on a Personalized Decision Control Algorithm for Autonomous Vehicles Based on the Reinforcement Learning from Human Feedback Strategy

Ning Li, Pengzhan Chen

To address the shortcomings of previous autonomous decision models, which often overlook the personalized features of users, this paper proposes a personalized decision control algorithm for autonomous vehicles based on RLHF (reinforcement learning from human feedback). The algor…Read more