3 papers
cs.LG2025
When to Trust Your Simulator: Dynamics-Aware Hybrid Offline-and-Online Reinforcement Learning
Haoyi Niu, Shubham Sharma, Yiwen Qiu +4
Learning effective reinforcement learning (RL) policies to solve real-world complex tasks can be quite challenging without a high-fidelity simulation environment. In most cases, we…
eess.SY2025
Moving Obstacle Collision Avoidance via Chance-Constrained MPC with CBF
Ming Li, Zhiyong Sun, Zirui Liao +1
Model predictive control (MPC) with control barrier functions (CBF) is a promising solution to address the moving obstacle collision avoidance (MOCA) problem. Unlike MPC with dista…
cs.CR2024
DP-BREM: Differentially-Private and Byzantine-Robust Federated Learning with Client Momentum
Xiaolan Gu, Ming Li, Li Xiong
Federated Learning (FL) allows multiple participating clients to train machine learning models collaboratively while keeping their datasets local and only exchanging the gradient o…