11 citations · 20 across the 5 of their papers we have counts for
5 papers
PASCAL: A Learning-aided Cooperative Bandwidth Control Policy for Hierarchical Storage Systems
Xijun Li, Yunfan Zhou, Ji Zhang
Nowadays, the Hierarchical Storage System (HSS) is considered as an ideal model to meet the cost-performance demand. The data migration between storing tiers of HSS is the way to a…
Offline Reinforcement Learning with Adaptive Behavior Regularization
Yunfan Zhou, Xijun Li, Qingyu Qu
Offline reinforcement learning (RL) defines a sample-efficient learning paradigm, where a policy is learned from static and previously collected datasets without additional interac…
Yordle: An Efficient Imitation Learning for Branch and Bound
Qingyu Qu, Xijun Li, Yunfan Zhou
Combinatorial optimization problems have aroused extensive research interests due to its huge application potential. In practice, there are highly redundant patterns and characteri…
An Improved Reinforcement Learning Algorithm for Learning to Branch
Qingyu Qu, Xijun Li, Yunfan Zhou +6
Most combinatorial optimization problems can be formulated as mixed integer linear programming (MILP), in which branch-and-bound (B\&B) is a general and widely used method. Recentl…
Learning to Optimize DAG Scheduling in Heterogeneous Environment
Jinhong Luo, Yunfan Zhou, Xijun Li +3
Scheduling job flows efficiently and rapidly on distributed computing clusters is one of huge challenges for daily operation of data centers. In a practical scenario, a single job…