9 citations · 9 across the 2 of their papers we have counts for
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cs.LG2023
UADB: Unsupervised Anomaly Detection Booster
Hangting Ye, Zhining Liu, Xinyi Shen +6
Unsupervised Anomaly Detection (UAD) is a key data mining problem owing to its wide real-world applications. Due to the complete absence of supervision signals, UAD methods rely on…
cs.LG2021★ 9 cited
Handling Inter-class and Intra-class Imbalance in Class-imbalanced Learning
Zhining Liu, Pengfei Wei, Zhepei Wei +5
Class-imbalance is a common problem in machine learning practice. Typical Imbalanced Learning (IL) methods balance the data via intuitive class-wise resampling or reweighting. Howe…