16 citations · 56 across the 25 of their papers we have counts for
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cs.LG2022★ 2 cited
You Can Have Better Graph Neural Networks by Not Training Weights at All: Finding Untrained GNNs Tickets
Tianjin Huang, Tianlong Chen, Meng Fang +8
Recent works have impressively demonstrated that there exists a subnetwork in randomly initialized convolutional neural networks (CNNs) that can match the performance of the fully…
cs.LG2022
FAL-CUR: Fair Active Learning using Uncertainty and Representativeness on Fair Clustering
Ricky Fajri, Akrati Saxena, Yulong Pei +1
Active Learning (AL) techniques have proven to be highly effective in reducing data labeling costs across a range of machine learning tasks. Nevertheless, one known challenge of th…
cs.LG2022★ 2 cited
Superposing Many Tickets into One: A Performance Booster for Sparse Neural Network Training
Lu Yin, Vlado Menkovski, Meng Fang +5
Recent works on sparse neural network training (sparse training) have shown that a compelling trade-off between performance and efficiency can be achieved by training intrinsically…