Shirui Pan
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Shirui Pan
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A Survey on Knowledge Graphs: Representation, Acquisition and Applications
Graph Learning: A Survey
Anomaly Detection on Attributed Networks via Contrastive Self-Supervised Learning
Convolutional Neural Networks based Lung Nodule Classification: A Surrogate-Assisted Evolutionary Algorithm for Hyperparameter Optimization
Learning Graph Neural Networks with Positive and Unlabeled Nodes
Task-adaptive Neural Process for User Cold-Start Recommendation
Contrastive and Generative Graph Convolutional Networks for Graph-based Semi-Supervised Learning
Compact Scheduling for Task Graph Oriented Mobile Crowdsourcing
One-Shot Neural Architecture Search: Maximising Diversity to Overcome Catastrophic Forgetting
Differentiable Neural Architecture Search in Equivalent Space with Exploration Enhancement
Graph Geometry Interaction Learning
Graph Stochastic Neural Networks for Semi-supervised Learning
Suicidal Ideation Detection: A Review of Machine Learning Methods and Applications
Cross-Graph: Robust and Unsupervised Embedding for Attributed Graphs with Corrupted Structure
OpenWGL: Open-World Graph Learning
Connecting the Dots: Multivariate Time Series Forecasting with Graph Neural Networks
Grounding Visual Concepts for Multimedia Event Detection and Multimedia Event Captioning in Zero-shot Setting
Multivariate Relations Aggregation Learning in Social Networks
Hyperspectral Image Classification with Context-aware Dynamic Graph Convolutional Networks
A Relation-Specific Attention Network for Joint Entity and Relation Extraction
One-Shot Neural Architecture Search via Novelty Driven Sampling
Reasoning Like Human: Hierarchical Reinforcement Learning for Knowledge Graph Reasoning
A comprehensive survey on graph neural networks
Overcoming Multi-Model Forgetting in One-Shot NAS with Diversity Maximization
Unsupervised Domain Adaptive Graph Convolutional Networks
Going Deep: Graph Convolutional Ladder-shape Networks
GSSNN: Graph Smoothing Splines Neural Networks
Reinforcement Learning based Meta-path Discovery in Large-scale Heterogeneous Information Networks
Clustering Social Audiences in Business Information Networks
Familial Clustering For Weakly-labeled Android Malware Using Hybrid Representation Learning
Adaptive knowledge subgraph ensemble for robust and trustworthy knowledge graph completion
An Effective and Explainable Deep Fusion Network for Affect Recognition Using Physiological Signals
Domain-Adversarial Graph Neural Networks for Text Classification
Learning Graph Embedding With Adversarial Training Methods
Long-short Distance Aggregation Networks for Positive Unlabeled Graph Learning
Relation Structure-Aware Heterogeneous Graph Neural Network
Exploiting Implicit Influence from Information Propagation for Social Recommendation
Attributed Graph Clustering: A Deep Attentional Embedding Approach
Graph WaveNet for Deep Spatial-Temporal Graph Modeling
Influence Spread in Geo-Social Networks: A Multi-Objective Optimization Perspective
Low-Bit Quantization for Attributed Network Representation Learning
CFOND: consensus factorization for co-clustering networked data
Cost-sensitive parallel learning framework for insurance intelligence operation
Detecting Suicidal Ideation with Data Protection in Online Communities
Identify topic relations in scientific literature using topic modeling
IEEE access special section editorial: advanced data analytics for large-scale complex data environments
Label Embedding with Partial Heterogeneous Contexts
Measuring distance-based semantic similarity using meronymy and hyponymy relations
Social recommendation with evolutionary opinion dynamics
Time series feature learning with labeled and unlabeled data
A hybrid user experience evaluation method for mobile games
A three-layered mutually reinforced model for personalized citation recommendation
Active discriminative network representation learning
Advances in processing, mining, and learning complex data: From foundations to real-world applications
Adversarially regularized graph autoencoder for graph embedding
Binarized attributed network embedding
Cost-sensitive hybrid neural networks for heterogeneous and imbalanced data
Cross-domain deep learning approach for multiple financial market prediction
DiSAN: directional self-attention network for RNN/CNN-free language understanding
Discrete network embedding
Explore semantic topics and author communities for citation recommendation in bipartite bibliographic network
FraudNE: a joint embedding approach for fraud detection
Hashing for adaptive real-time graph stream classification with concept drifts
Heterogeneous information network embedding based personalized query-focused astronomy reference paper recommendation
Low-rank and sparse matrix factorization for scientific paper recommendation in heterogeneous network
Multi-instance learning with discriminative bag mapping
Multiple structure-view learning for graph classification
Query-oriented citation recommendation based on network correlation
Supervised learning for suicidal ideation detection in online user content
Boosting for graph classification with universum
Graph ladder networks for network classification
MGAE: marginalized graph autoencoder for graph clustering
Multi-document summarization based on sentence cluster using Non-negative Matrix Factorization
Positive and unlabeled multi-graph learning
Task sensitive feature exploration and learning for multitask graph classification
Towards large-scale social networks with online diffusion provenance detection
Universal network representation for heterogeneous information networks
Classifying networked text data with positive and unlabeled examples
Co-clustering enterprise social networks
Direct discriminative bag mapping for multi-instance learning
Iterative views agreement: an iterative low-rank based structured optimization method to multi-view spectral clustering
Joint structure feature exploration and regularization for multi-task graph classification
Multi-graph-view subgraph mining for graph classification
SODE: Self-adaptive one-dependence estimators for classification
Tri-party deep network representation
Boosting for multi-graph classification
CogBoost: boosting for fast cost-sensitive graph classification
Finding the best not the most: regularized loss minimization subgraph selection for graph classification
Graph ensemble boosting for imbalanced noisy graph stream classification
Locally weighted learning: how and when does it work in Bayesian networks?
Mining top-k minimal redundancy frequent patterns over uncertain databases
Multi-graph-view learning for complicated object classification
Multi-graph-view Learning for Graph Classification
Self-adaptive attribute weighting for Naive Bayes classification
Attribute weighting: how and when does it work for Bayesian Network Classification
Dual instance and attribute weighting for Naive Bayes classification
Exploring features for complicated objects: cross-view feature selection for multi-instance learning
Multi-graph learning with positive and unlabeled bags
Graph classification with imbalanced class distributions and noise
Graph stream classification using labeled and unlabeled graphs
CGStream: Continuous correlated graph query for data streams
Continuous top-k query for graph streams
Dynamic classifier ensemble for positive unlabeled text stream classification
Top-k correlated subgraph query for data streams
Classifier ensemble for uncertain data stream classification
Ensemble of multiple descriptors for automatic image annotation
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