no-regret-learning

This paper introduces OCO-PAoI-Hard, an online convex optimization framework for multi-sensor IoT scheduling that enforces hard per-slot peak Age-of-Information deadlines under adversarial channels, achieving zero modeled-state deadline violations and O(√T) regret.