1 citations · 2 across the 9 of their papers we have counts for
5 papers · 1 filter
Federated Continual Learning as a Distributed Drift-Plus-Penalty Control Problem
Nazreen Shah, Naveen Kumar Reddy Somireddy, Zubair Shaban +2
Federated Continual Learning (FCL) is fundamental to real-world distributed learning systems, requiring models to adapt to sequential, non-IID data across clients while mitigating…
Channel-Adaptive Robust Aggregation for Over-the-Air Federated Learning in Heterogeneous Networks
Zubaida Fatima, Zubair Shaban, Yusuf Jamal +3
The growing demand for privacy-preserving, data-intensive applications such as IoT, augmented reality, and autonomous systems positions Federated Learning (FL) as a key enabler in…
Theoretical Foundations of Continual Learning via Drift-Plus-Penalty
Nazreen Shah, Govinda Arya, Bharath B. N. +1
In many real-world settings, data streams are nonstationary and arrive sequentially, requiring learning systems to adapt continuously without retraining from scratch. Continual lea…
Informative Perturbation Selection for Uncertainty-Aware Post-hoc Explanations
Sumedha Chugh, Ranjitha Prasad, Nazreen Shah
Trust and ethical concerns due to the widespread deployment of opaque machine learning (ML) models motivating the need for reliable model explanations. Post-hoc model-agnostic expl…
Nishpaksh: TEC Standard-Compliant Framework for Fairness Auditing and Certification of AI Models
Shashank Prakash, Ranjitha Prasad, Avinash Agarwal
The growing reliance on Artificial Intelligence (AI) models in high-stakes decision-making systems, particularly within emerging telecom and 6G applications, underscores the urgent…