52 citations · 143 across the 13 of their papers we have counts for
20 papers
Graph Convolution Based Efficient Re-Ranking for Visual Retrieval
Yuqi Zhang, Qi Qian, Hongsong Wang +3
Visual retrieval tasks such as image retrieval and person re-identification (Re-ID) aim at effectively and thoroughly searching images with similar content or the same identity. Af…
Semantic Data Augmentation based Distance Metric Learning for Domain Generalization
Mengzhu Wang, Jianlong Yuan, Qi Qian +2
Domain generalization (DG) aims to learn a model on one or more different but related source domains that could be generalized into an unseen target domain. Existing DG methods try…
An Empirical Study on Distribution Shift Robustness From the Perspective of Pre-Training and Data Augmentation
Ziquan Liu, Yi Xu, Yuanhong Xu +5
The performance of machine learning models under distribution shift has been the focus of the community in recent years. Most of current methods have been proposed to improve the r…
Dash: Semi-Supervised Learning with Dynamic Thresholding
Yi Xu, Lei Shang, Jinxing Ye +5
While semi-supervised learning (SSL) has received tremendous attentions in many machine learning tasks due to its successful use of unlabeled data, existing SSL algorithms use eith…
Why Does Multi-Epoch Training Help?
Yi Xu, Qi Qian, Hao Li +1
Stochastic gradient descent (SGD) has become the most attractive optimization method in training large-scale deep neural networks due to its simplicity, low computational cost in e…
A Theoretical Analysis of Learning with Noisily Labeled Data
Yi Xu, Qi Qian, Hao Li +1
Noisy labels are very common in deep supervised learning. Although many studies tend to improve the robustness of deep training for noisy labels, rare works focus on theoretically…