Publications (5)
AxPUE: Application Level Metrics for Power Usage Effectiveness in Data Centers
Runlin Zhou, Yingjie Shi, Chunge Zhu +1
The rapid growth of data volume brings big challenges to the data center computing, and energy efficiency is one of the most concerned problems. Researchers from various fields are…
Row-wise Fusion Regularization: An Interpretable Personalized Federated Learning Framework in Large-Scale Scenarios
Runlin Zhou, Letian Li, Zemin Zheng
We study personalized federated learning for multivariate responses where client models are heterogeneous yet share variable-level structure. Existing entry-wise penalties ignore c…
Prior-Aligned Meta-RL: Thompson Sampling with Learned Priors and Guarantees in Finite-Horizon MDPs
Runlin Zhou, Chixiang Chen, Elynn Chen
We study meta-reinforcement learning in finite-horizon MDPs where related tasks share similar structures in their optimal action-value functions. Specifically, we posit a linear re…
Industrial Surface Defect Detection via Diffusion Generation and Asymmetric Student-Teacher Network
Shuo Feng, Runlin Zhou, Yuyang Li +1
Industrial surface defect detection often suffers from limited defect samples, severe long-tailed distributions, and difficulties in accurately localizing subtle defects under comp…
The Implications of Diverse Applications and Scalable Data Sets in Benchmarking Big Data Systems
Zhen Jia, Runlin Zhou, Chunge Zhu +5
Now we live in an era of big data, and big data applications are becoming more and more pervasive. How to benchmark data center computer systems running big data applications (in s…