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Jia Wu
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Towards Flexible and Adaptive Neural Process for Cold-Start Recommendation
A Survey of Community Detection Approaches: From Statistical Modeling to Deep Learning
Task-adaptive Neural Process for User Cold-Start Recommendation
Graph Geometry Interaction Learning
Graph Stochastic Neural Networks for Semi-supervised Learning
Adaptive knowledge subgraph ensemble for robust and trustworthy knowledge graph completion
IEEE access special section editorial: advanced data analytics for large-scale complex data environments
Time series feature learning with labeled and unlabeled data
Active discriminative network representation learning
Advances in processing, mining, and learning complex data: From foundations to real-world applications
FraudNE: a joint embedding approach for fraud detection
Multi-instance learning with discriminative bag mapping
Multiple structure-view learning for graph classification
Boosting for graph classification with universum
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
Direct discriminative bag mapping for multi-instance learning
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
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