78 citations · 144 across the 9 of their papers we have counts for
Showing 2020 · cs.LGShow all
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cs.LG2020
MESA: Boost Ensemble Imbalanced Learning with MEta-SAmpler
Zhining Liu, Pengfei Wei, Jing Jiang +3
Imbalanced learning (IL), i.e., learning unbiased models from class-imbalanced data, is a challenging problem. Typical IL methods including resampling and reweighting were designed…
cs.LG2020
GraphLIME: Local Interpretable Model Explanations for Graph Neural Networks
Qiang Huang, Makoto Yamada, Yuan Tian +3
Graph structured data has wide applicability in various domains such as physics, chemistry, biology, computer vision, and social networks, to name a few. Recently, graph neural net…