GAugur: Quantifying Performance Interference of Colocated Games for Improving Resource Utilization in Cloud Gaming. - Yusen Li; Chuxu Shan; Ruobing Chen 002; Xueyan Tang; Wentong Cai 001; Shanjiang Tang; Xiaoguang Liu 001; Gang Wang 001; Xiaoli Gong; Ying Zhang 015 (HPDC, 2019)

Deep Learning Assisted Resource Partitioning for Improving Performance on Commodity Servers. - Ruobing Chen 002; Jinping Wu; Haosen Shi 001; Yusen Li; Haiyan Yin; Shanjiang Tang; Xiaoguang Liu 001; Gang Wang 001 (PACT, 2020)

DRLPart: A Deep Reinforcement Learning Framework for Optimally Efficient and Robust Resource Partitioning on Commodity Servers. - Ruobing Chen 002; Jinping Wu; Haosen Shi 001; Yusen Li; Xiaoguang Liu 001; Gang Wang 001 (HPDC, 2021)

GCNPart: Interference-Aware Resource Partitioning Framework with Graph Convolutional Neural Networks and Deep Reinforcement Learning. - Ruobing Chen 002; Haosen Shi 001; Jinping Wu; Yusen Li; Xiaoguang Liu 001; Gang Wang 001 (ICA3PP, 2022)

OLPart: Online Learning based Resource Partitioning for Colocating Multiple Latency-Critical Jobs on Commodity Computers. - Ruobing Chen 002; Haosen Shi 001; Yusen Li; Xiaoguang Liu 001; Gang Wang 001 (EuroSys, 2023)

CoTuner: A Hierarchical Learning Framework for Coordinately Optimizing Resource Partitioning and Parameter Tuning. - Tiannuo Yang; Ruobing Chen 002; Yusen Li; Xiaoguang Liu 001; Gang Wang 001 (ICPP, 2023)

Jointly Optimizing Job Assignment and Resource Partitioning for Improving System Throughput in Cloud Datacenters. - Ruobing Chen 002; Haosen Shi 001; Jinping Wu; Yusen Li; Xiaoguang Liu 001; Gang Wang 001 (ACM Trans. Archit. Code Optim., 2023)

Orchid: An Online Learning Based Resource Partitioning Framework for Job Colocation With Multiple Objectives. - Ruobing Chen 002; Wangqi Peng; Yusen Li; Xiaoguang Liu 001; Gang Wang 001 (IEEE Trans. Computers, 2023)