3 papers
cs.LG2025
Toward Robust and Efficient ML-Based GPU Caching for Modern Inference
Peng Chen, Jiaji Zhang, Hailiang Zhao +11
In modern GPU inference, cache efficiency remains a major bottleneck, and heuristic policies such as \textsc{LRU} can perform far worse than the offline optimum. Existing learning-…
cs.DS2025
Robustifying Learning-Augmented Caching Efficiently without Compromising 1-Consistency
Peng Chen, Hailiang Zhao, Jiaji Zhang +3
The online caching problem aims to minimize cache misses when serving a sequence of requests under a limited cache size. While naive learning-augmented caching algorithms achieve i…
cs.LG2024
Learning-Augmented Algorithms for the Bahncard Problem
Hailiang Zhao, Xueyan Tang, Peng Chen +1
In this paper, we study learning-augmented algorithms for the Bahncard problem. The Bahncard problem is a generalization of the ski-rental problem, where a traveler needs to irrevo…