Area of research
Statistics and Probability · Artificial Intelligence
Research interest
Research interests include Face and Expression Recognition, Statistical Methods and Bayesian Inference, Quantum Information and Cryptography, and Advanced Clustering Algorithms Research.
Scalable tri-factorization guided multi-view subspace clustering
Towards multi-fusion graph neural network for single-cell RNA sequence clustering
Large-Scale Tensorized Multi-View Kernel Subspace Clustering
Structure-preserving contrastive graph clustering with dual-channel label alignment
Multi-scale Multi-order Attributed Graph Clustering
Unified and Tensorized Incomplete Multi-View Kernel Subspace Clustering
Tensorized Incomplete Multi-view Kernel Subspace Clustering
Confidence-oriented Contrastive Graph Clustering
Motorcyclist helmet detection in single images: a dual-detection framework with multi-head self-attention
Seeking commonness and inconsistencies: A jointly smoothed approach to multi-view subspace clustering
Facilitated low-rank multi-view subspace clustering
A bi-layer decomposition algorithm for many-objective optimization problems
Kernelized multi-view subspace clustering via auto-weighted graph learning
Multiple Imputation of Missing Data in Practice
Consistency- and Inconsistency-Aware Multi-view Subspace Clustering
Joint representation learning for multi-view subspace clustering
One-step Kernel Multi-view Subspace Clustering
TW-Co-k-means: Two-level weighted collaborative k-means for multi-view clustering
Multi-view collaborative locally adaptive clustering with Minkowski metric
Weighted Multi-view On-Line Competitive Clustering