Area of research
Artificial Intelligence · Automotive Engineering
Research interest
Research focused on Embedding and Autoencoder, with related work in Graph, Constraint (computer-aided design), Social network (sociolinguistics). Notable publications include 'Deep Dynamic Network Embedding for Link Prediction', 'Sub-Graph Contrast for Scalable Self-Supervised Graph Representation Learning', and 'Graph Representation Learning'.
Graph Representation Learning
A bi-level cooperative operation approach for AGV based automated valet parking
Hyperbolic Variational Graph Neural Network for Modeling Dynamic Graphs
Ripple Walk Training: A Subgraph-based Training Framework for Large and Deep Graph Neural Network
Label Contrastive Coding based Graph Neural Network for Graph Classification
BGADAM: Boosting based Genetic-Evolutionary ADAM for Neural Network Optimization
Sub-Graph Contrast for Scalable Self-Supervised Graph Representation Learning
Sub-graph Contrast for Scalable Self-Supervised Graph Representation Learning
BANANA: when Behavior ANAlysis meets social Network Alignment
Ripple Walk Training: A Subgraph-based training framework for Large and Deep Graph Neural Network
DEAM: Adaptive Momentum with Discriminative Weight for Stochastic Optimization
Discovering Localized Information for Heterogeneous Graph Node Representation Learning
Collective Link Prediction Oriented Network Embedding with Hierarchical Graph Attention
Meta Diagram Based Active Social Networks Alignment
Broad Learning Through Fusions
Machine Learning Overview
EnsemFDet: An Ensemble Approach to Fraud Detection based on Bipartite Graph
Deep Heterogeneous Social Network Alignment
Semi-supervised Network Alignment
Collective Link Prediction Oriented Network Embedding with Hierarchical Graph Attention
DEAM: Adaptive Momentum with Discriminative Weight for Stochastic Optimization
Supervised Network Alignment
Deep Dynamic Network Embedding for Link Prediction
A data-based model for driving distance estimation of battery electric logistics vehicles
A Self-Organizing Tensor Architecture for Multi-view Clustering
Data-driven Blockbuster Planning on Online Movie Knowledge Library
BL-MNE: Emerging Heterogeneous Social Network Embedding Through Broad Learning with Aligned Autoencoder
Contaminant removal for Android malware detection systems
Constrained Active Learning for Anchor Link Prediction Across Multiple Heterogeneous Social Networks
Inverse extreme learning machine for learning with label proportions