11 papers
Diffusion-Guided Semantic Consistency for Multimodal Heterogeneity
Jing Liu, Zhengliang Guo, Yan Wang +4
Federated learning (FL) is severely challenged by non-independent and identically distributed (non-IID) client data, a problem that degrades global model performance, especially in…
Edge-Cloud Collaborative Computing on Distributed Intelligence and Model Optimization: A Survey
Jing Liu, Yao Du, Kun Yang +8
Edge-cloud collaborative computing (ECCC) has emerged as a pivotal paradigm for addressing the computational demands of modern intelligent applications, integrating cloud resources…
Toward a Sustainable Federated Learning Ecosystem: A Practical Least Core Mechanism for Payoff Allocation
Zhengwei Ni, Zhidu Li, Wei Chen +4
Emerging network paradigms and applications increasingly rely on federated learning (FL) to enable collaborative intelligence while preserving privacy. However, the sustainability…
A Survey on Cloud-Edge-Terminal Collaborative Intelligence in AIoT Networks
Jiaqi Wu, Jing Liu, Yang Liu +6
The proliferation of Internet of things (IoT) devices in smart cities, transportation, healthcare, and industrial applications, coupled with the explosive growth of AI-driven servi…
A Novel Approach to Differential Privacy with Alpha Divergence
Yifeng Liu, Zehua Wang
As data-driven technologies advance swiftly, maintaining strong privacy measures becomes progressively difficult. Conventional -differential privacy, while prevalent, exh…
A Survey on Diffusion Models for Anomaly Detection
Jing Liu, Zhenchao Ma, Zepu Wang +7
Diffusion models (DMs) have emerged as a powerful class of generative AI models, showing remarkable potential in anomaly detection (AD) tasks across various domains, such as cybers…