53 citations · 94 across the 6 of their papers we have counts for
6 papers
Self-supervised Learning for Heterogeneous Graph via Structure Information based on Metapath
Shuai Ma, Jian-wei Liu, Xin Zuo
graph neural networks (GNNs) are the dominant paradigm for modeling and handling graph structure data by learning universal node representation. The traditional way of training GNN…
Multi-Scale Iterative Refinement Network for RGB-D Salient Object Detection
Ze-yu Liu, Jian-wei Liu, Xin Zuo +1
The extensive research leveraging RGB-D information has been exploited in salient object detection. However, salient visual cues appear in various scales and resolutions of RGB ima…
Online Deep Learning based on Auto-Encoder
Si-si Zhang, Jian-wei Liu, Xin Zuo +2
Online learning is an important technical means for sketching massive real-time and high-speed data. Although this direction has attracted intensive attention, most of the literatu…
Multi-View representation learning in Multi-Task Scene
Run-kun Lu, Jian-wei Liu, Si-ming Lian +1
Over recent decades have witnessed considerable progress in whether multi-task learning or multi-view learning, but the situation that consider both learning scenes simultaneously…
Auto-Encoder based Co-Training Multi-View Representation Learning
Run-kun Lu, Jian-wei Liu, Yuan-fang Wang +2
Multi-view learning is a learning problem that utilizes the various representations of an object to mine valuable knowledge and improve the performance of learning algorithm, and o…
Adaptive Online Incremental Learning for Evolving Data Streams
Si-si Zhang, Jian-wei Liu, Xin Zuo
Recent years have witnessed growing interests in online incremental learning. However, there are three major challenges in this area. The first major difficulty is concept drift, t…