Optimistic Learning with Applications to Caching Networks
Ph.D. thesis on optimistic online learning with applications to caching networks.
Online Caching with no Regret: Optimistic Learning via Recommendations
An optimistic learning framework for online caching that leverages recommendations to improve regret without sacrificing worst-case guarantees.
Optimistic No-regret Algorithms for Discrete Caching
No-regret algorithms for discrete caching that integrate untrusted predictions for improved performance.
Online Caching with Optimistic Learning
Online caching with optimistic learning, exploiting predictions while keeping no-regret guarantees.