A
Albert Y. Zomaya
Researcher at University of Sydney
Publications - 1020
Citations - 30827
Albert Y. Zomaya is an academic researcher from University of Sydney. The author has contributed to research in topics: Cloud computing & Scheduling (computing). The author has an hindex of 75, co-authored 946 publications receiving 24637 citations. Previous affiliations of Albert Y. Zomaya include University of Alabama & University of Sheffield.
Papers
More filters
Book ChapterDOI
Energy Efficiency Evaluation of Distributed Systems
TL;DR: PowerSave is developed as a lightweight software framework that enables dynamic reconfiguration of power limits and shows that for workloads typical of servers used in data centers, higher power caps correlate with higher overall CPU energy use.
Posted Content
DONE: Distributed Approximate Newton-type Method for Federated Edge Learning.
TL;DR: In this article, a distributed approximate Newton-type algorithm with fast convergence rate for communication-efficient federated edge learning is proposed, and the experimental results with non-i.i.d and heterogeneous data show that DONE attains a comparable performance to the Newton's method.
Proceedings ArticleDOI
An efficient VLSI architecture parallel prefix counting with domino logic
TL;DR: An efficient reconfigurable parallel prefix counting network based on the recently-proposed technique of shift switching with domino logic, where the charge/discharge signals propagate along the switch chain producing semaphores results in a network that is fast and highly hardware-compact.
Journal ArticleDOI
High Performance Computing for Robot Dynamic Parameters Learning
TL;DR: In this paper, the authors propose a method for the computation of the actuating forces/torques in order to provide the desired motion of the end effector, which is directly dependent on the accuracy of the dynamic model.
Journal ArticleDOI
A Composite Multi-Attention Framework for Intraoperative Hypotension Early Warning
Feng Lu,Wei Liu,Zhiqiang Zhou,Cheng Song,Yu Ren,Xiaofei Liao,Hai Jin,Ailin Luo,Albert Y. Zomaya +8 more
TL;DR: In this article , a composite multi-attention (CMA) framework is proposed to predict intraoperative hypotension (IOH) events using vital signals in a low sampling rate with demographic characteristics.