I used hill climbing to tune TinyLFU. A larger admission window improves recency-biased workloads, while a smaller improves for frequency. By sampling the hit r

I used hill climbing to tune TinyLFU. A larger admission window improves recency-biased workloads, while a smaller improves for frequency. By sampling the hit rate and making an initial adjustment, it can determine when to change directions and hone in on the best configuration. Other than a small warm-up penalty, it quickly optimizes itself.