Self-Paced Active Learning: Query the Right Thing at the Right Time. - Ying-Peng Tang; Sheng-Jun Huang (AAAI, 2019)

ALiPy: Active Learning in Python. - Ying-Peng Tang; Guo-Xiang Li; Sheng-Jun Huang (CoRR, 2019)

Dual Active Learning for Both Model and Data Selection. - Ying-Peng Tang; Sheng-Jun Huang (IJCAI, 2021)

Active Learning for Multiple Target Models. - Ying-Peng Tang; Sheng-Jun Huang (NeurIPS, 2022)

A Survey of Learning on Small Data. - Xiaofeng Cao 002; Weixin Bu; Shengjun Huang; Ying-Peng Tang; Yaming Guo; Yi Chang 001; Ivor W. Tsang (CoRR, 2022)

MUS-CDB: Mixed Uncertainty Sampling With Class Distribution Balancing for Active Annotation in Aerial Object Detection. - Dong Liang 008; Jing-Wei Zhang; Ying-Peng Tang; Sheng-Jun Huang (IEEE Trans. Geosci. Remote. Sens., 2023)

QBox: Partial Transfer Learning With Active Querying for Object Detection. - Ying-Peng Tang; Xiu-Shen Wei; Borui Zhao; Sheng-Jun Huang (IEEE Trans. Neural Networks Learn. Syst., 2023)

One-shot Active Learning Based on Lewis Weight Sampling for Multiple Deep Models. - Sheng-Jun Huang; Yi Li; Yiming Sun; Ying-Peng Tang (ICLR, 2024)