3 papers
cs.CV2026
Privacy-Preserving Federated Action Recognition via Differentially Private Selective Tuning and Efficient Communication
Idris Zakariyya, Pai Chet Ng, Kaushik Bhargav Sivangi +3
Federated video action recognition enables collaborative model training without sharing raw video data, yet remains vulnerable to two key challenges: \textit{model exposure} and \t…
cs.LG2025
Quantitative Analysis of Deeply Quantized Tiny Neural Networks Robust to Adversarial Attacks
Idris Zakariyya, Ferheen Ayaz, Mounia Kharbouche-Harrari +4
Reducing the memory footprint of Machine Learning (ML) models, especially Deep Neural Networks (DNNs), is imperative to facilitate their deployment on resource-constrained edge dev…
cs.LG2023
Improving Robustness Against Adversarial Attacks with Deeply Quantized Neural Networks
Ferheen Ayaz, Idris Zakariyya, José Cano +4
Reducing the memory footprint of Machine Learning (ML) models, particularly Deep Neural Networks (DNNs), is essential to enable their deployment into resource-constrained tiny devi…