14 citations · 26 across the 4 of their papers we have counts for
5 papers
Unsupervised Representation Learning for Time Series: A Review
Qianwen Meng, Hangwei Qian, Yong Liu +3
Unsupervised representation learning approaches aim to learn discriminative feature representations from unlabeled data, without the requirement of annotating every sample. Enablin…
MHCCL: Masked Hierarchical Cluster-Wise Contrastive Learning for Multivariate Time Series
Qianwen Meng, Hangwei Qian, Yong Liu +3
Learning semantic-rich representations from raw unlabeled time series data is critical for downstream tasks such as classification and forecasting. Contrastive learning has recentl…
Enhancing Sequential Recommendation with Graph Contrastive Learning
Yixin Zhang, Yong Liu, Yonghui Xu +5
The sequential recommendation systems capture users' dynamic behavior patterns to predict their next interaction behaviors. Most existing sequential recommendation methods only exp…
Time-aware Graph Embedding: A temporal smoothness and task-oriented approach
Yonghui Xu, Shengjie Sun, Yuan Miao +6
Knowledge graph embedding, which aims to learn the low-dimensional representations of entities and relationships, has attracted considerable research efforts recently. However, mos…
Contextualized Graph Attention Network for Recommendation with Item Knowledge Graph
Susen Yang, Yong Liu, Yonghui Xu +3
Graph neural networks (GNN) have recently been applied to exploit knowledge graph (KG) for recommendation. Existing GNN-based methods explicitly model the dependency between an ent…