5 papers
Parameter Stress Analysis in Reinforcement Learning: Applying Synaptic Filtering to Policy Networks
Zain ul Abdeen, Ming Jin
This paper explores reinforcement learning (RL) policy robustness by systematically analyzing network parameters under internal and external stresses. \textcolor{black}{We apply sy…
Toward Adaptive Grid Resilience: A Gradient-Free Meta-RL Framework for Critical Load Restoration
Zain ul Abdeen, Waris Gill, Ming Jin
Restoring critical loads after extreme events demands adaptive control to maintain distribution-grid resilience, yet uncertainty in renewable generation, limited dispatchable resou…
Cloud Revolution: Tracing the Origins and Rise of Cloud Computing
Deepa Gurung, S M Zia Ur Rashid, Zain ul Abdeen +1
The history behind the development of cloud computing is more than several decades of technological progress in the fields of virtualization, distributed systems, and high-speed ne…
A Scalable Approach for Safe and Robust Learning via Lipschitz-Constrained Networks
Zain ul Abdeen, Vassilis Kekatos, Ming Jin
Certified robustness is a critical property for deploying neural networks (NN) in safety-critical applications. A principle approach to achieving such guarantees is to constrain th…
IP-FL: Incentivized and Personalized Federated Learning
Ahmad Faraz Khan, Xinran Wang, Qi Le +7
Existing incentive solutions for traditional Federated Learning (FL) focus on individual contributions to a single global objective, neglecting the nuances of clustered personaliza…