- 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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