A theory-driven self-labeling refinement method for contrastive representation learning

by ZHOU, Pan, XIONG, Caiming, YUAN, Xiao-Tong
Published 2021

Prototypical contrastive learning of unsupervised representations

by LI, Junnan, ZHOU, Pan, XIONG, Caiming, HOI, Steven C. H.
Published 2021

Theory-inspired path-regularized differential network architecture search

by ZHOU, Pan, XIONG, Caiming, SOCHER, Richard, HOI, Steven C. H.
Published 2020

Towards theoretically understanding why SGD generalizes better than ADAM in deep learning

by ZHOU, Pan, FENG, Jiashi, MA, Chao, XIONG, Caiming, HOI, Steven C. H., E, Weinan
Published 2020

Task similarity aware meta learning: Theory-inspired improvement on MAML

by ZHOU, Pan, ZPU, Yingtian, YUAN, XiaoTong, FENG, Jiashi, XIONG, Caiming, HOI, Steven C. H.
Published 2021

Improving tail-class representation with centroid contrastive learning

by Tiong, Anthony Meng Huat, Li, Junnan, Lin, Guosheng, Li, Boyang, Xiong, Caiming, Hoi, Steven C. H.
Published 2023

How important is the train-validation split in meta-learning?

by BAI, Yu, CHEN, Minshuo, ZHOU, Pan, ZHAO, Tuo, LEE, D. Jason, KAKADE, Sham, WANG, Huan, XIONG, Caiming
Published 2021