4 citations · 5 across the 10 of their papers we have counts for
Showing cs.LGShow all
2 papers · 1 filter
cs.LG2023
GIMM: InfoMin-Max for Automated Graph Contrastive Learning
Xin Xiong, Furao Shen, Xiangyu Wang +1
Graph contrastive learning (GCL) shows great potential in unsupervised graph representation learning. Data augmentation plays a vital role in GCL, and its optimal choice heavily de…
cs.LG2021
Inf-CP: A Reliable Channel Pruning based on Channel Influence
Bilan Lai, Haoran Xiang, Furao Shen
One of the most effective methods of channel pruning is to trim on the basis of the importance of each neuron. However, measuring the importance of each neuron is an NP-hard proble…