output
20172026
most citedSCEI: A Smart-Contract Driven Edge Intelligence Framework for IoT Systems

19 citations

6 papers

eess.SP2026★ 8 cited

A General Framework for Generative Self-supervised Learning in Non-invasive Estimation of Physiological Parameters Using Photoplethysmography

Zexing Zhang, Huimin Lu, Songzhe Ma +4

Aligning physiological parameter labels with large-scale photoplethysmographic (PPG) data for deep learning is challenging and resource-intensive. While self-supervised representat…

cond-mat.mtrl-sci2026

Symmetry-directed electronic and optical properties in a two-dimensional square-lattice ZnPc-MOF

Zhonghui Han, Lanting Feng, Guodong Yu +1

The electronic structure of materials is fundamentally governed by their crystal symmetry. While most research on two-dimensional materials has focused on hexagonal lattices, such…

physics.app-ph2022★ 2 cited

Research status and prospect of graphene materials in aviation

S. Y. Gao, Y. F. Jiang, J. W. Sun +1

Among various 2D materials, graphene has received extensive research attention in the past 2-30 years due to its fascinating properties. The discovery of graphene has provided a hu…

cs.LG2021★ 19 cited

SCEI: A Smart-Contract Driven Edge Intelligence Framework for IoT Systems

Chenhao Xu, Jiaqi Ge, Yong Li +5

Federated learning (FL) enables collaborative training of a shared model on edge devices while maintaining data privacy. FL is effective when dealing with independent and identical…

math.QA2020

Pre-Lie analogues of Poisson-Nijenhuis structures and Maurer-Cartan equations

Jiefeng Liu, Qi Wang

In this paper, we study pre-Lie analogues of Poisson-Nijenhuis structures and introduce ON-structures on bimodules over pre-Lie algebras. We show that an ON-structure gives rise to…

stat.ME2017

Weighted empirical likelihood for quantile regression with nonignorable missing covariates

Xiaohui Yuan, Xiaogang Dong

In this paper, we propose an empirical likelihood-based weighted estimator of regression parameter in quantile regression model with nonignorable missing covariates. The proposed e…