10 papers
Efficient Transceiver Design for Aerial Image Transmission and Large-scale Scene Reconstruction
Zeyi Ren, Jialin Dong, Wei Zuo +4
Large-scale three-dimensional (3D) scene reconstruction in low-altitude intelligent networks (LAIN) demands highly efficient wireless image transmission. However, existing schemes…
NTK-Guided Implicit Neural Teaching
Chen Zhang, Wei Zuo, Bingyang Cheng +4
Implicit Neural Representations (INRs) parameterize continuous signals via multilayer perceptrons (MLPs), enabling compact, resolution-independent modeling for tasks like image, au…
Nonparametric Teaching of Attention Learners
Chen Zhang, Jianghui Wang, Bingyang Cheng +7
Attention learners, neural networks built on the attention mechanism, e.g., transformers, excel at learning the implicit relationships that relate sequences to their corresponding…
HPTune: Hierarchical Proactive Tuning for Collision-Free Model Predictive Control
Wei Zuo, Chengyang Li, Yikun Wang +5
Parameter tuning is a powerful approach to enhance adaptability in model predictive control (MPC) motion planners. However, existing methods typically operate in a myopic fashion t…
Large-Scale Bayesian Tensor Reconstruction: An Approximate Message Passing Solution
Bingyang Cheng, Zhongtao Chen, Yichen Jin +4
Tensor CANDECOMP/PARAFAC decomposition (CPD) is a fundamental model for tensor reconstruction. Although the Bayesian framework allows for principled uncertainty quantification and…
FedDSR: Federated Deep Supervision and Regularization Towards Autonomous Driving
Wei-Bin Kou, Guangxu Zhu, Bingyang Cheng +3
Federated Learning (FL) enables collaborative training of autonomous driving (AD) models across distributed vehicles while preserving data privacy. However, FL encounters critical…