18 citations · 44 across the 12 of their papers we have counts for
15 papers
Deep graph convolution neural network with non-negative matrix factorization for community discovery
Shuliang Xu, Shenglan Liu, Lin Feng
Community discovery is an important task for graph mining. Owing to the nonstructure, the high dimensionality, and the sparsity of graph data, it is not easy to obtain an appropria…
Self-Supervised Deep Graph Embedding with High-Order Information Fusion for Community Discovery
Shuliang Xu, Shenglan Liu, Lin Feng
Deep graph embedding is an important approach for community discovery. Deep graph neural network with self-supervised mechanism can obtain the low-dimensional embedding vectors of…
Multimodal-Aware Weakly Supervised Metric Learning with Self-weighting Triplet Loss
Huiyuan Deng, Xiangzhu Meng, Lin Feng
In recent years, we have witnessed a surge of interests in learning a suitable distance metric from weakly supervised data. Most existing methods aim to pull all the similar sample…
Multi-view Low-rank Preserving Embedding: A Novel Method for Multi-view Representation
Xiangzhu Meng, Lin Feng, Huibing Wang
In recent years, we have witnessed a surge of interest in multi-view representation learning, which is concerned with the problem of learning representations of multi-view data. Wh…
FSD-10: A Dataset for Competitive Sports Content Analysis
Shenlan Liu, Xiang Liu, Gao Huang +6
Action recognition is an important and challenging problem in video analysis. Although the past decade has witnessed progress in action recognition with the development of deep lea…
The Similarity-Consensus Regularized Multi-view Learning for Dimension Reduction
Xiangzhu Meng, Huibing Wang, Lin Feng
During the last decades, learning a low-dimensional space with discriminative information for dimension reduction (DR) has gained a surge of interest. However, it's not accessible…