No-Regret Caching via Online Mirror Descent.

2021 
We study an online caching problem in which requests can be served by a local cache to avoid retrieval costs from a remote server. The cache can update its state after a batch of requests and store an arbitrarily small fraction of each content. We study no-regret algorithms based on Online Mirror Descent (OMD) strategies. We show that the optimal OMD strategy depends on the request diversity present in a batch. We also prove that, when the cache must store the entire content, rather than a fraction, OMD strategies can be coupled with a randomized rounding scheme that preserves regret guarantees.
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