… Despite its success in many areas, deep learning is a … deep learning to help design a new
cache replacement policy. We first show that for cache replacement, a powerful LSTM learning …

… the generation of a cache replacement policy that is … use Reinforcement Learning (RL) to
learn a cache replacement policy. … For the cache replacement problem targeted in this work, we …

… depends on increasing cache hits, as cache hits are orders of magnitude faster than misses.
To increase cache hits, we focus on the problem of cache replacement: choosing which …

… machine learning tools to the problem of content caching. In that, using such a framework,
we proposed how to reason about the cache prediction problem … existing cache replacement …

… machine learning to cache replacement [1], [3], [10]–[12]. This study confirmed the applicability
of machine learning… we formulate cache replacement as a probabilistic prediction problem …

… subsets of artificial intelligence that have been applied to solve web caching problems [86]. …
deep learning-based web cache replacement models perform better than machine learning …

… advances in machine learning to guide cache replacement policy, augmenting or … problems
encountered in this paper. We consider cache replacement as a decision-making problem …

… and optimize cache placement and replacement strategies provided … These applications of
machine learning can help identify … The key research problems regarding caching at the edge …

… Optimization of caching placement/replacement and content … for caching optimization, from
a deep learning perspective. The … In this section, we consider a joint caching problem for …

… Lin, “Applying deep learning to the cache replacement problem,” in Proceedings of the
52nd Annual IEEE/ACM International Symposium on Microarchitecture, ser. MICRO ’52. …