105 citations · 218 across the 26 of their papers we have counts for
8 papers · 1 filter
Topological Structure Learning for Weakly-Supervised Out-of-Distribution Detection
Rundong He, Rongxue Li, Zhongyi Han +1
Out-of-distribution (OOD) detection is the key to deploying models safely in the open world. For OOD detection, collecting sufficient in-distribution (ID) labeled data is usually m…
Self-Filtering: A Noise-Aware Sample Selection for Label Noise with Confidence Penalization
Qi Wei, Haoliang Sun, Xiankai Lu +1
Sample selection is an effective strategy to mitigate the effect of label noise in robust learning. Typical strategies commonly apply the small-loss criterion to identify clean sam…
DRNet: Decomposition and Reconstruction Network for Remote Physiological Measurement
Yuhang Dong, Gongping Yang, Yilong Yin
Remote photoplethysmography (rPPG) based physiological measurement has great application values in affective computing, non-contact health monitoring, telehealth monitoring, etc, w…
Neural Network Compression via Effective Filter Analysis and Hierarchical Pruning
Ziqi Zhou, Li Lian, Yilong Yin +1
Network compression is crucial to making the deep networks to be more efficient, faster, and generalizable to low-end hardware. Current network compression methods have two open pr…
Active Source Free Domain Adaptation
Fan Wang, Zhongyi Han, Zhiyan Zhang +1
Source free domain adaptation (SFDA) aims to transfer a trained source model to the unlabeled target domain without accessing the source data. However, the SFDA setting faces an ef…
Exploring Linear Feature Disentanglement For Neural Networks
Tiantian He, Zhibin Li, Yongshun Gong +3
Non-linear activation functions, e.g., Sigmoid, ReLU, and Tanh, have achieved great success in neural networks (NNs). Due to the complex non-linear characteristic of samples, the o…