16 citations · 41 across the 6 of their papers we have counts for
9 papers
Self-paced Principal Component Analysis
Zhao Kang, Hongfei Liu, Jiangxin Li +2
Principal Component Analysis (PCA) has been widely used for dimensionality reduction and feature extraction. Robust PCA (RPCA), under different robust distance metrics, such as l1-…
Self-paced Resistance Learning against Overfitting on Noisy Labels
Xiaoshuang Shi, Zhenhua Guo, Kang Li +2
Noisy labels composed of correct and corrupted ones are pervasive in practice. They might significantly deteriorate the performance of convolutional neural networks (CNNs), because…
Structured Graph Learning for Scalable Subspace Clustering: From Single-view to Multi-view
Zhao Kang, Zhiping Lin, Xiaofeng Zhu +1
Graph-based subspace clustering methods have exhibited promising performance. However, they still suffer some of these drawbacks: encounter the expensive time overhead, fail in exp…
Joint Prediction and Time Estimation of COVID-19 Developing Severe Symptoms using Chest CT Scan
Xiaofeng Zhu, Bin Song, Feng Shi +9
With the rapidly worldwide spread of Coronavirus disease (COVID-19), it is of great importance to conduct early diagnosis of COVID-19 and predict the time that patients might conve…
Neural Network Retraining for Model Serving
Diego Klabjan, Xiaofeng Zhu
We propose incremental (re)training of a neural network model to cope with a continuous flow of new data in inference during model serving. As such, this is a life-long learning pr…
Listwise Learning to Rank by Exploring Unique Ratings
Xiaofeng Zhu, Diego Klabjan
In this paper, we propose new listwise learning-to-rank models that mitigate the shortcomings of existing ones. Existing listwise learning-to-rank models are generally derived from…