66 citations · 107 across the 16 of their papers we have counts for
4 papers · 1 filter
Learning to Fine-tune Foundation Models under Resource Limitations
Thomas Tsouparopoulos, Iordanis Koutsopoulos
We study the problem of optimal continual fine-tuning for a pre-trained Foundation Model deployed at a resource-limited device. At each time slot, a new batch of training data arri…
Explainability and Continual Learning meet Federated Learning at the Network Edge
Thomas Tsouparopoulos, Iordanis Koutsopoulos
As edge devices become more capable and pervasive in wireless networks, there is growing interest in leveraging their collective compute power for distributed learning. However, op…
Joint Explainability-Performance Optimization With Surrogate Models for AI-Driven Edge Services
Foivos Charalampakos, Thomas Tsouparopoulos, Iordanis Koutsopoulos
Explainable AI is a crucial component for edge services, as it ensures reliable decision making based on complex AI models. Surrogate models are a prominent approach of XAI where h…
Personalized Federated Learning with Exact Stochastic Gradient Descent
Sotirios Nikoloutsopoulos, Iordanis Koutsopoulos, Michalis K. Titsias
We propose a Stochastic Gradient Descent (SGD)-type algorithm for Personalized Federated Learning which can be particularly attractive for mobile energy-limited regimes due to its…