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cs.LG2022★ 1 cited
Calibrate and Debias Layer-wise Sampling for Graph Convolutional Networks
Yifan Chen, Tianning Xu, Dilek Hakkani-Tur +3
Multiple sampling-based methods have been developed for approximating and accelerating node embedding aggregation in graph convolutional networks (GCNs) training. Among them, a lay…
cs.LG2021
Sketching as a Tool for Understanding and Accelerating Self-attention for Long Sequences
Yifan Chen, Qi Zeng, Dilek Hakkani-Tur +3
Transformer-based models are not efficient in processing long sequences due to the quadratic space and time complexity of the self-attention modules. To address this limitation, Li…