activity
20222024
most citedResource Allocation for Mobile Metaverse with the Internet of Vehicles over 6G Wireless Communications: A Deep Reinforcement Learning Approach

1 citations · 1 across the 3 of their papers we have counts for

collaborators

7 papers

cs.ET2024

A Unified Successive Approximation Framework for General Coupled Multiplicative and Fractional Optimization: HM-GM-AM-QM Transforms and Applications

Liangxin Qian, Wenhan Yu, Peiyuan Si +4

Optimization problems in communication networks and information systems often contain coupled multiplicative or fractional terms, such as sum-of-products, sum-of-ratios, and logari…

cs.CR2024

PrivTuner with Homomorphic Encryption and LoRA: A P3EFT Scheme for Privacy-Preserving Parameter-Efficient Fine-Tuning of AI Foundation Models

Yang Li, Wenhan Yu, Jun Zhao

AI foundation models have recently demonstrated impressive capabilities across a wide range of tasks. Fine-tuning (FT) is a method of customizing a pre-trained AI foundation model…

cs.NI2023

Mobile Edge Computing and AI Enabled Web3 Metaverse over 6G Wireless Communications: A Deep Reinforcement Learning Approach

Wenhan Yu, Terence Jie Chua, Jun Zhao

The Metaverse is gaining attention among academics as maturing technologies empower the promises and envisagements of a multi-purpose, integrated virtual environment. An interactiv…

cs.AI2023

Orchestration of Emulator Assisted Mobile Edge Tuning for AI Foundation Models: A Multi-Agent Deep Reinforcement Learning Approach

Wenhan Yu, Terence Jie Chua, Jun Zhao

The efficient deployment and fine-tuning of foundation models are pivotal in contemporary artificial intelligence. In this study, we present a groundbreaking paradigm integrating M…

cs.LG2023

FedPEAT: Convergence of Federated Learning, Parameter-Efficient Fine Tuning, and Emulator Assisted Tuning for Artificial Intelligence Foundation Models with Mobile Edge Computing

Terence Jie Chua, Wenhan Yu, Jun Zhao +1

The emergence of foundation models, including language and vision models, has reshaped AI's landscape, offering capabilities across various applications. Deploying and fine-tuning…

cs.NI2023

Heterogeneous 360 Degree Videos in Metaverse: Differentiated Reinforcement Learning Approaches

Wenhan Yu, Jun Zhao

Advanced video technologies are driving the development of the futuristic Metaverse, which aims to connect users from anywhere and anytime. As such, the use cases for users will be…