3 citations · 3 across the 3 of their papers we have counts for
4 papers
PRIVEE: Privacy-Preserving Vertical Federated Learning Against Feature Inference Attacks
Sindhuja Madabushi, Haider Ali, Ahmad Faraz Khan +5
Vertical Federated Learning (VFL) enables collaborative model training across organizations that share common user samples but hold disjoint feature spaces. Despite its potential,…
Assessing the Impact of Code Changes on the Fault Localizability of Large Language Models
Sabaat Haroon, Ahmad Faraz Khan, Ahmad Humayun +5
Generative Large Language Models (LLMs) are increasingly used in non-generative software maintenance tasks, such as fault localization (FL). Success in FL depends on a models abili…
FLStore: Efficient Federated Learning Storage for non-training workloads
Ahmad Faraz Khan, Samuel Fountain, Ahmed M. Abdelmoniem +2
Federated Learning (FL) is an approach for privacy-preserving Machine Learning (ML), enabling model training across multiple clients without centralized data collection. With an ag…
LADs: Leveraging LLMs for AI-Driven DevOps
Ahmad Faraz Khan, Azal Ahmad Khan, Anas Mohamed +7
Automating cloud configuration and deployment remains a critical challenge due to evolving infrastructures, heterogeneous hardware, and fluctuating workloads. Existing solutions la…