29 citations · 207 across the 17 of their papers we have counts for
19 papers
Hierarchical Skeleton Meta-Prototype Contrastive Learning with Hard Skeleton Mining for Unsupervised Person Re-Identification
Haocong Rao, Cyril Leung, Chunyan Miao
With rapid advancements in depth sensors and deep learning, skeleton-based person re-identification (re-ID) models have recently achieved remarkable progress with many advantages.…
Can ChatGPT Assess Human Personalities? A General Evaluation Framework
Haocong Rao, Cyril Leung, Chunyan Miao
Large Language Models (LLMs) especially ChatGPT have produced impressive results in various areas, but their potential human-like psychology is still largely unexplored. Existing w…
Inductive Graph Transformer for Delivery Time Estimation
Xin Zhou, Jinglong Wang, Yong Liu +3
Providing accurate estimated time of package delivery on users' purchasing pages for e-commerce platforms is of great importance to their purchasing decisions and post-purchase exp…
Exploring Representation-Level Augmentation for Code Search
Haochen Li, Chunyan Miao, Cyril Leung +4
Code search, which aims at retrieving the most relevant code fragment for a given natural language query, is a common activity in software development practice. Recently, contrasti…
A Dynamic Hierarchical Framework for IoT-assisted Metaverse Synchronization
Yue Han, Dusit Niyato, Cyril Leung +5
Metaverse has recently attracted much attention from both academia and industry. Virtual services, ranging from virtual driver training to online route optimization for smart goods…
A Dynamic Resource Allocation Framework for Synchronizing Metaverse with IoT Service and Data
Yue Han, Dusit Niyato, Cyril Leung +2
Spurred by the severe restrictions on mobility due to the COVID-19 pandemic, there is currently intense interest in developing the Metaverse, to offer virtual services/business onl…
Dynamics in Coded Edge Computing for IoT: A Fractional Evolutionary Game Approach
Yue Han, Dusit Niyato, Cyril Leung +2
Recently, coded distributed computing (CDC), with advantages in intensive computation and reduced latency, has attracted a lot of research interest for edge computing, in particula…
A Contract Theory based Incentive Mechanism for Federated Learning
Mengmeng Tian, Yuxin Chen, Yuan Liu +3
Federated learning (FL) serves as a data privacy-preserved machine learning paradigm, and realizes the collaborative model trained by distributed clients. To accomplish an FL task,…
A Game-theoretic Approach Towards Collaborative Coded Computation Offloading
Jer Shyuan Ng, Wei Yang Bryan Lim, Zehui Xiong +5
Coded distributed computing (CDC) has emerged as a promising approach because it enables computation tasks to be carried out in a distributed manner while mitigating straggler effe…
Collaborative Coded Computation Offloading: An All-pay Auction Approach
Jer Shyuan Ng, Wei Yang Bryan Lim, Sahil Garg +4
As the amount of data collected for crowdsensing applications increases rapidly due to improved sensing capabilities and the increasing number of Internet of Things (IoT) devices,…
Optimal Transaction Queue Waiting in Blockchain Mining
Gholamreza Ramezan, Cyril Leung, Chunyan Miao
Blockchain systems are being used in a wide range of application domains. They can support trusted transactions in time critical applications. In this paper, we study how miners sh…
A Survey of Coded Distributed Computing
Jer Shyuan Ng, Wei Yang Bryan Lim, Nguyen Cong Luong +5
Distributed computing has become a common approach for large-scale computation of tasks due to benefits such as high reliability, scalability, computation speed, and costeffectiven…
Scalable and Communication-efficient Decentralized Federated Edge Learning with Multi-blockchain Framework
Jiawen Kang, Zehui Xiong, Chunxiao Jiang +6
The emerging Federated Edge Learning (FEL) technique has drawn considerable attention, which not only ensures good machine learning performance but also solves "data island" proble…
Joint Auction-Coalition Formation Framework for Communication-Efficient Federated Learning in UAV-Enabled Internet of Vehicles
Jer Shyuan Ng, Wei Yang Bryan Lim, Hong-Ning Dai +6
Due to the advanced capabilities of the Internet of Vehicles (IoV) components such as vehicles, Roadside Units (RSUs) and smart devices as well as the increasing amount of data gen…
Incentive Mechanism Design for Resource Sharing in Collaborative Edge Learning
Wei Yang Bryan Lim, Jer Shyuan Ng, Zehui Xiong +4
In 5G and Beyond networks, Artificial Intelligence applications are expected to be increasingly ubiquitous. This necessitates a paradigm shift from the current cloud-centric model…
Towards Federated Learning in UAV-Enabled Internet of Vehicles: A Multi-Dimensional Contract-Matching Approach
Wei Yang Bryan Lim, Jianqiang Huang, Zehui Xiong +5
Coupled with the rise of Deep Learning, the wealth of data and enhanced computation capabilities of Internet of Vehicles (IoV) components enable effective Artificial Intelligence (…
Ethically Aligned Opportunistic Scheduling for Productive Laziness
Han Yu, Chunyan Miao, Yongqing Zheng +3
In artificial intelligence (AI) mediated workforce management systems (e.g., crowdsourcing), long-term success depends on workers accomplishing tasks productively and resting well.…
Building Ethics into Artificial Intelligence
Han Yu, Zhiqi Shen, Chunyan Miao +3
As artificial intelligence (AI) systems become increasingly ubiquitous, the topic of AI governance for ethical decision-making by AI has captured public imagination. Within the AI…
A game theory approach for self-coexistence analysis among IEEE 802.22 networks
Dong Huang, Zhiqi Shen, Chunyan Miao +2
This paper has been withdrawn by the author due to some errors