Ke Liang

According to our database, Ke Liang authored at least 34 papers between 2021 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

Simple Contrastive Graph Clustering.

Yue Liu, Xihong Yang, Sihang Zhou, Xinwang Liu, Siwei Wang, Ke Liang, Wenxuan Tu, Liang Li

IEEE Trans. Neural Networks Learn. Syst., October, 2024

High-order Topology for Deep Single-Cell Multiview Fuzzy Clustering.

Dayu Hu, Zhibin Dong, Ke Liang, Hao Yu, Siwei Wang, Xinwang Liu

IEEE Trans. Fuzzy Syst., August, 2024

Knowledge Graph Contrastive Learning Based on Relation-Symmetrical Structure.

Ke Liang, Yue Liu, Sihang Zhou, Wenxuan Tu, Yi Wen, Xihong Yang, Xiangjun Dong, Xinwang Liu

IEEE Trans. Knowl. Data Eng., January, 2024

Post-Semantic-Thinking: A Robust Strategy to Distill Reasoning Capacity from Large Language Models.

Xiaoshu Chen, Sihang Zhou, Ke Liang, Xinwang Liu

CoRR, 2024

Don't Turn a Blind Eye to Localization Noise: Localization Pseudo-label Correction and Learning for Semi-Supervised Object Detection.

Yulin He, Wei Chen, Zhengfa Liang, Ke Liang, Yusong Tan, Tianrui Liu, Yulan Guo

Proceedings of the IEEE International Conference on Multimedia and Expo, 2024

Deep Temporal Graph Clustering.

Meng Liu, Yue Liu, Ke Liang, Wenxuan Tu, Siwei Wang, Sihang Zhou, Xinwang Liu

Proceedings of the Twelfth International Conference on Learning Representations, 2024

Learn from View Correlation: An Anchor Enhancement Strategy for Multi-View Clustering.

Suyuan Liu, Ke Liang, Zhibin Dong, Siwei Wang, Xihong Yang, Sihang Zhou, En Zhu, Xinwang Liu

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2024

MINES: Message Intercommunication for Inductive Relation Reasoning over Neighbor-Enhanced Subgraphs.

Ke Liang, Lingyuan Meng, Sihang Zhou, Wenxuan Tu, Siwei Wang, Yue Liu, Meng Liu, Long Zhao, Xiangjun Dong, Xinwang Liu

Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

Hawkes-Enhanced Spatial-Temporal Hypergraph Contrastive Learning Based on Criminal Correlations.

Ke Liang, Sihang Zhou, Meng Liu, Yue Liu, Wenxuan Tu, Yi Zhang, Liming Fang, Zhe Liu, Xinwang Liu

Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

2023

ABSLearn: a GNN-based framework for aliasing and buffer-size information retrieval.

Ke Liang, Jim Tan, Dongrui Zeng, Yongzhe Huang, Xiaolei Huang, Gang Tan

Pattern Anal. Appl., August, 2023

scDFC: A deep fusion clustering method for single-cell RNA-seq data.

Dayu Hu, Ke Liang, Sihang Zhou, Wenxuan Tu, Meng Liu, Xinwang Liu

Briefings Bioinform., July, 2023

Single-Cell Clustering via Dual-Graph Alignment.

Dayu Hu, Ke Liang, Xinwang Liu

CoRR, 2023

Single-cell Multi-view Clustering via Community Detection with Unknown Number of Clusters.

Dayu Hu, Zhibin Dong, Ke Liang, Jun Wang, Siwei Wang, Xinwang Liu

CoRR, 2023

Structure Guided Multi-modal Pre-trained Transformer for Knowledge Graph Reasoning.

Ke Liang, Sihang Zhou, Yue Liu, Lingyuan Meng, Meng Liu, Xinwang Liu

CoRR, 2023

Unpaired Multi-View Graph Clustering with Cross-View Structure Matching.

Yi Wen, Siwei Wang, Qing Liao, Weixuan Liang, Ke Liang, Xinhang Wan, Xinwang Liu

CoRR, 2023

arXiv4TGC: Large-Scale Datasets for Temporal Graph Clustering.

Meng Liu, Ke Liang, Yue Liu, Siwei Wang, Sihang Zhou, Xinwang Liu

CoRR, 2023

Message Intercommunication for Inductive Relation Reasoning.

Ke Liang, Lingyuan Meng, Sihang Zhou, Siwei Wang, Wenxuan Tu, Yue Liu, Meng Liu, Xinwang Liu

CoRR, 2023

Deep Temporal Graph Clustering.

Meng Liu, Yue Liu, Ke Liang, Siwei Wang, Sihang Zhou, Xinwang Liu

CoRR, 2023

SARF: Aliasing Relation Assisted Self-Supervised Learning for Few-shot Relation Reasoning.

Lingyuan Meng, Ke Liang, Bin Xiao, Sihang Zhou, Yue Liu, Meng Liu, Xihong Yang, Xinwang Liu

CoRR, 2023

Pseudo-label Correction and Learning For Semi-Supervised Object Detection.

Yulin He, Wei Chen, Ke Liang, Yusong Tan, Zhengfa Liang, Yulan Guo

CoRR, 2023

Self-Supervised Temporal Graph learning with Temporal and Structural Intensity Alignment.

Meng Liu, Ke Liang, Bin Xiao, Sihang Zhou, Wenxuan Tu, Yue Liu, Xihong Yang, Xinwang Liu

CoRR, 2023

Learn from Relational Correlations and Periodic Events for Temporal Knowledge Graph Reasoning.

Ke Liang, Lingyuan Meng, Meng Liu, Yue Liu, Wenxuan Tu, Siwei Wang, Sihang Zhou, Xinwang Liu

Proceedings of the 46th International ACM SIGIR Conference on Research and Development in Information Retrieval, 2023

CONVERT: Contrastive Graph Clustering with Reliable Augmentation.

Xihong Yang, Cheng Tan, Yue Liu, Ke Liang, Siwei Wang, Sihang Zhou, Jun Xia, Stan Z. Li, Xinwang Liu, En Zhu

Proceedings of the 31st ACM International Conference on Multimedia, 2023

DealMVC: Dual Contrastive Calibration for Multi-view Clustering.

Xihong Yang, Jiaqi Jin, Siwei Wang, Ke Liang, Yue Liu, Yi Wen, Suyuan Liu, Sihang Zhou, Xinwang Liu, En Zhu

Proceedings of the 31st ACM International Conference on Multimedia, 2023

Scalable Incomplete Multi-View Clustering with Structure Alignment.

Yi Wen, Siwei Wang, Ke Liang, Weixuan Liang, Xinhang Wan, Xinwang Liu, Suyuan Liu, Jiyuan Liu, En Zhu

Proceedings of the 31st ACM International Conference on Multimedia, 2023

Efficient Multi-View Graph Clustering with Local and Global Structure Preservation.

Yi Wen, Suyuan Liu, Xinhang Wan, Siwei Wang, Ke Liang, Xinwang Liu, Xihong Yang, Pei Zhang

Proceedings of the 31st ACM International Conference on Multimedia, 2023

Reinforcement Graph Clustering with Unknown Cluster Number.

Yue Liu, Ke Liang, Jun Xia, Xihong Yang, Sihang Zhou, Meng Liu, Xinwang Liu, Stan Z. Li

Proceedings of the 31st ACM International Conference on Multimedia, 2023

TMac: Temporal Multi-Modal Graph Learning for Acoustic Event Classification.

Meng Liu, Ke Liang, Dayu Hu, Hao Yu, Yue Liu, Lingyuan Meng, Wenxuan Tu, Sihang Zhou, Xinwang Liu

Proceedings of the 31st ACM International Conference on Multimedia, 2023

Dink-Net: Neural Clustering on Large Graphs.

Yue Liu, Ke Liang, Jun Xia, Sihang Zhou, Xihong Yang, Xinwang Liu, Stan Z. Li

Proceedings of the International Conference on Machine Learning, 2023

Hard Sample Aware Network for Contrastive Deep Graph Clustering.

Yue Liu, Xihong Yang, Sihang Zhou, Xinwang Liu, Zhen Wang, Ke Liang, Wenxuan Tu, Liang Li, Jingcan Duan, Cancan Chen

Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

2022

Reasoning over Different Types of Knowledge Graphs: Static, Temporal and Multi-Modal.

Ke Liang, Lingyuan Meng, Meng Liu, Yue Liu, Wenxuan Tu, Siwei Wang, Sihang Zhou, Xinwang Liu, Fuchun Sun

CoRR, 2022

A Survey of Deep Graph Clustering: Taxonomy, Challenge, and Application.

Yue Liu, Jun Xia, Sihang Zhou, Siwei Wang, Xifeng Guo, Xihong Yang, Ke Liang, Wenxuan Tu, Stan Z. Li, Xinwang Liu

CoRR, 2022

Relational Symmetry based Knowledge Graph Contrastive Learning.

Ke Liang, Yue Liu, Sihang Zhou, Xinwang Liu, Wenxuan Tu

CoRR, 2022

2021

Machine Learning Applications in the Routing in Computer Networks.

Ke Liang, Mitchel Myers

CoRR, 2021