Zhao Yang

Orcid: 0000-0002-9525-2096

Affiliations:
  • Chang'an University, School of Future Transportation, Xi'an, China


According to our database1, Zhao Yang authored at least 14 papers between 2021 and 2026.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of four.

Timeline

Legend:

Book  In proceedings  Article  PhD thesis  Dataset  Other 

Links

Online presence:

On csauthors.net:

Bibliography

2026
Automated federated aggregation for dynamic systems and data in mobile edge computing.
Future Gener. Comput. Syst., 2026

2024
Energy-Efficient Personalized Federated Continual Learning on Edge.
IEEE Embed. Syst. Lett., December, 2024

NDPGNN: A Near-Data Processing Architecture for GNN Training and Inference Acceleration.
IEEE Trans. Comput. Aided Des. Integr. Circuits Syst., November, 2024

Equalized Aggregation for Heterogeneous Federated Mobile Edge Learning.
IEEE Trans. Mob. Comput., May, 2024

Efficient knowledge management for heterogeneous federated continual learning on resource-constrained edge devices.
Future Gener. Comput. Syst., 2024

OFT: An accelerator with eager gradient prediction for attention training.
Proceedings of the 43rd IEEE/ACM International Conference on Computer-Aided Design, 2024

Resource-Efficient Heterogenous Federated Continual Learning on Edge.
Proceedings of the Design, Automation & Test in Europe Conference & Exhibition, 2024

2023
Energy-efficient Personalized Federated Search with Graph for Edge Computing.
ACM Trans. Embed. Comput. Syst., October, 2023

Joint heterogeneity-aware personalized federated search for energy efficient battery-powered edge computing.
Future Gener. Comput. Syst., 2023

SaGNN: a Sample-based GNN Training and Inference Hardware Accelerator.
Proceedings of the IEEE International Symposium on Circuits and Systems, 2023

2022
Memory-Computing Decoupling: A DNN Multitasking Accelerator With Adaptive Data Arrangement.
IEEE Trans. Comput. Aided Des. Integr. Circuits Syst., 2022

DCNN search and accelerator co-design: Improve the adaptability between NAS frameworks and embedded platforms.
Integr., 2022

A dynamic global backbone updating for communication-efficient personalised federated learning.
Connect. Sci., 2022

2021
Hardware-Aware NAS Framework with Layer Adaptive Scheduling on Embedded System.
Proceedings of the ASPDAC '21: 26th Asia and South Pacific Design Automation Conference, 2021


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