38 citations · 105 across the 16 of their papers we have counts for
17 papers
Toward efficient resource utilization at edge nodes in federated learning
Sadi Alawadi, Addi Ait-Mlouk, Salman Toor +1
Federated learning (FL) enables edge nodes to collaboratively contribute to constructing a global model without sharing their data. This is accomplished by devices computing local,…
Accelerating Fair Federated Learning: Adaptive Federated Adam
Li Ju, Tianru Zhang, Salman Toor +1
Federated learning is a distributed and privacy-preserving approach to train a statistical model collaboratively from decentralized data of different parties. However, when dataset…
To test, or not to test: A proactive approach for deciding complete performance test initiation
Omar Javed, Prashant Singh, Giles Reger +1
Software performance testing requires a set of inputs that exercise different sections of the code to identify performance issues. However, running tests on a large set of inputs c…
FedQAS: Privacy-aware machine reading comprehension with federated learning
Addi Ait-Mlouk, Sadi Alawadi, Salman Toor +1
Machine reading comprehension (MRC) of text data is one important task in Natural Language Understanding. It is a complex NLP problem with a lot of ongoing research fueled by the r…
Efficient Hierarchical Storage Management Framework Empowered by Reinforcement Learning
Tianru Zhang, Salman Toor, Andreas Hellander
With the rapid development of big data and cloud computing, data management has become increasingly challenging. Over the years, a number of frameworks for data management and stor…
Proactive Autoscaling for Edge Computing Systems with Kubernetes
Li Ju, Prashant Singh, Salman Toor
With the emergence of the Internet of Things and 5G technologies, the edge computing paradigm is playing increasingly important roles with better availability, latency-control and…