An Empirical Study and Analysis on Open-Set Semi-Supervised Learning

no code implementations • 19 Jan 2021 • Huixiang Luo, Hao Cheng, Fanxu Meng, Yuting Gao, Ke Li, Mengdan Zhang, Xing Sun

Pseudo-labeling (PL) and Data Augmentation-based Consistency Training (DACT) are two approaches widely used in Semi-Supervised Learning (SSL) methods.

Data Augmentation

Pruning Filter in Filter

1 code implementation • NeurIPS 2020 • Fanxu Meng, Hao Cheng, Ke Li, Huixiang Luo, Xiaowei Guo, Guangming Lu, Xing Sun

Through extensive experiments, we demonstrate that SWP is more effective compared to the previous FP-based methods and achieves the state-of-art pruning ratio on CIFAR-10 and ImageNet datasets without obvious accuracy drop.