no code implementations • 27 Apr 2024 • Dou Liu, Ying Han, Xiandi Wang, Xiaomei Tan, Di Liu, Guangwu Qian, Kang Li, Dan Pu, Rong Yin
However, the between-version consistency is relatively low (mean consistency score=1. 43/3, median=1), indicating few recommendations match between the two versions.
no code implementations • 10 Dec 2023 • Ruyue Liu, Rong Yin, Yong liu, Weiping Wang
Graph Comparative Learning (GCL) is a self-supervised method that combines the advantages of Graph Convolutional Networks (GCNs) and comparative learning, making it promising for learning node representations.
no code implementations • NeurIPS 2018 • Jian Li, Yong liu, Rong Yin, Hua Zhang, Lizhong Ding, Weiping Wang
In this paper, we study the generalization performance of multi-class classification and obtain a shaper data-dependent generalization error bound with fast convergence rate, substantially improving the state-of-art bounds in the existing data-dependent generalization analysis.