collaborators

5 papers

eess.SP2026

Distributed Precoding for Cell-free Massive MIMO in O-RAN: A Multi-agent Deep Reinforcement Learning Framework

Mohammad Hossein Shokouhi, Vincent W. S. Wong

Cell-free massive multiple-input multiple-output (MIMO) is a key technology for next-generation wireless systems. The integration of cell-free massive MIMO within the open radio ac…

cs.LG2026

FLoRG: Federated Fine-tuning with Low-rank Gram Matrices and Procrustes Alignment

Chuiyang Meng, Ming Tang, Vincent W. S. Wong

Parameter-efficient fine-tuning techniques such as low-rank adaptation (LoRA) enable large language models (LLMs) to adapt to downstream tasks efficiently. Federated learning (FL)…

cs.LG2026

ASFL: An Adaptive Model Splitting and Resource Allocation Framework for Split Federated Learning

Chuiyang Meng, Ming Tang, Vincent W. S. Wong

Federated learning (FL) enables multiple clients to collaboratively train a machine learning model without sharing their raw data. However, the limited computation resources of the…

cs.LG2026

ZorBA: Zeroth-order Federated Fine-tuning of LLMs with Heterogeneous Block Activation

Chuiyang Meng, Ming Tang, Vincent W. S. Wong

Federated fine-tuning of large language models (LLMs) enables collaborative tuning across distributed clients. However, due to the large size of LLMs, local updates in federated le…

eess.IV2024

Viewport Prediction, Bitrate Selection, and Beamforming Design for THz-Enabled 360° Video Streaming

Mehdi Setayesh, Vincent W. S. Wong

360° videos require significant bandwidth to provide an immersive viewing experience. Wireless systems using terahertz (THz) frequency band can meet this high data rate demand. Ho…