283 citations · 343 across the 7 of their papers we have counts for
7 papers
Tutel: Adaptive Mixture-of-Experts at Scale
Changho Hwang, Wei Cui, Yifan Xiong +12
Sparsely-gated mixture-of-experts (MoE) has been widely adopted to scale deep learning models to trillion-plus parameters with fixed computational cost. The algorithmic performance…
Scalable Deep Reinforcement Learning for Routing and Spectrum Access in Physical Layer
Wei Cui, Wei Yu
This paper proposes a novel scalable reinforcement learning approach for simultaneous routing and spectrum access in wireless ad-hoc networks. In most previous works on reinforceme…
Spatial Deep Learning for Wireless Scheduling
Wei Cui, Kaiming Shen, Wei Yu
The optimal scheduling of interfering links in a dense wireless network with full frequency reuse is a challenging task. The traditional method involves first estimating all the in…
Bufferless transmission in complex networks
Cunlai Pu, Wei Cui, Jiexin Wu +1
Complex bufferless networks such as on-chip networks and optical burst switching networks haven't been paid enough attention in network science. In complex bufferless networks, the…
Information transmission on hybrid networks
Rongbin Chen, Wei Cui, Cunlai Pu +4
Many real-world communication networks often have hybrid nature with both fixed nodes and moving modes, such as the mobile phone networks mainly composed of fixed base stations and…
Bounded link prediction for very large networks
Wei Cui, Cunlai Pu, Zhongqi Xu
Evaluation of link prediction methods is a hard task in very large complex networks because of the inhibitive computational cost. By setting a lower bound of the number of common n…