2 papers
cs.LG2025
Efficient and Optimal No-Regret Caching under Partial Observation
Younes Ben Mazziane, Francescomaria Faticanti, Sara Alouf +1
Online learning algorithms have been successfully used to design caching policies with sublinear regret in the total number of requests, with no statistical assumption about the re…
cs.LG2024
An Online Gradient-Based Caching Policy with Logarithmic Complexity and Regret Guarantees
Damiano Carra, Giovanni Neglia
Commonly used caching policies, such as LRU (Least Recently Used) or LFU (Least Frequently Used), exhibit optimal performance only under specific traffic patterns. Even advanced ma…