11 papers
Partially Lazy Gradient Descent for Smoothed Online Learning
Naram Mhaisen, George Iosifidis
We introduce \textsc{-lazyGD}, an online learning algorithm that bridges the gap between greedy Online Gradient Descent (OGD, for ) and lazy GD/dual-averaging (for $k{=}T…
Constrained Online Convex Optimization with Memory and Predictions
Mohammed Abdullah, George Iosifidis, Salah Eddine Elayoubi +1
We study Constrained Online Convex Optimization with Memory (COCO-M), where both the loss and the constraints depend on a finite window of past decisions made by the learner. This…
On the Dynamic Regret of Following the Regularized Leader: Optimism with History Pruning
Naram Mhaisen, George Iosifidis
We revisit the Follow the Regularized Leader (FTRL) framework for Online Convex Optimization (OCO) over compact sets, focusing on achieving dynamic regret guarantees. Prior work ha…
Equitable Multi-Task Learning for AI-RANs
Panayiotis Raptis, Fatih Aslan, George Iosifidis
AI-enabled Radio Access Networks (AI-RANs) are expected to serve heterogeneous users with time-varying learning tasks over shared edge resources. Ensuring equitable inference perfo…
Meta-Learning-Based Handover Management in NextG O-RAN
Michail Kalntis, George Iosifidis, José Suárez-Varela +2
While traditional handovers (THOs) have served as a backbone for mobile connectivity, they increasingly suffer from failures and delays, especially in dense deployments and high-fr…
CHOMET: Conditional Handovers via Meta-Learning
Michail Kalntis, Fernando A. Kuipers, George Iosifidis
Handovers (HOs) are the cornerstone of modern cellular networks for enabling seamless connectivity to a vast and diverse number of mobile users. However, as mobile networks become…