Papers › On the Regret of Online Coded Caching
On the Regret of Online Coded Caching
Anupam Nayak, Sheel Shah, Nikhil Karamchandani
The archive published only this paper's code-link row. Authors, date and abstract are from arXiv's metadata (CC0), read from the Kaggle arXiv metadata snapshot of 2026-09-12 where its title matched the archive's; the title is the archive's.
We consider the widely studied problem of coded caching under non-uniform requests where users independently request files according to some underlying popularity distribution in each slot. This work is a first step towards analyzing this framework through the lens of online learning. We consider the case where the underlying request distribution is apriori unknown and propose an online policy as well as study its regret with respect to an oracle which knows the underlying distribution and employs a well-known order-optimal placement and coded delivery strategy. We also bound the switching cost of this strategy and also discuss a lower bound on the regret of any online scheme in a restricted but natural class of policies.
Code
Repository list and official/mentioned flags are the archive's, frozen 2025-07-28. Reachability, where shown, is from one Syntology probe window (2026-09-16 to 2026-09-18); repositories not probed show nothing. GitHub stars are not tracked.
Code Syntology ran Syntology
Not run by Syntology. Nothing on this page verifies that the listed code works.
Results from the paper archive 2025-07-28
No leaderboard rows for this paper in the archive.
Report a problem or propose a change · a person checks every report against the paper or source before anything changes; decisions are listed on /corrections