Knowledge Science with Learning and AI
Joint Feature Selection and Classifier Parameter Optimization: A Bio-inspired Approach
Automatic Gaussian Bandwidth Selection for Kernel Principal Component Analysis
Boosting LightWeight Depth Estimation Via Knowledge Distillation
Graph Neural Network with Neighborhood Reconnection
Critical Node Privacy Protection Based on Random Pruning of Critical Trees
DSEAformer: Forecasting by De-stationary Autocorrelation with Edgebound
Multitask-based Cluster Transmission for Few-Shot Text Classification
Hyperplane Knowledge Graph Embedding with Path Neighborhoods and Mapping Properties
RTAD-TP: Real- Time Anomaly Detection Algorithm for Univariate Time Series Data Based on Two- Parameter Estimation
Multi-Sampling Item Response Ranking Neural Cognitive Diagnosis with Bilinear Feature Interaction
A Sparse Matrix Optimization Method for Graph Neural Networks Training
Dual-dimensional Refinement of Knowledge Graph Embedding Representation
Contextual Information Augmented Few-Shot Relation Extraction
Dynamic and Static Feature-aware Microservices Decomposition via Graph Neural Networks
An Enhanced Fitness-distance Balance Slime Mould Algorithm and Its Application in Feature Selection
Low Redundancy Learning for Unsupervised Multi-view Feature Selection
Dynamic Feed-Forward LSTM
Black-box Adversarial Attack on Graph Neural Networks Based on Node Domain Knowledge
Role and Relationship-Aware Representation Learning for Complex Coupled Dynamic Heterogeneous Networks
Twin Graph Attention Network with Evolution Pattern Learner for Few-Shot Temporal Knowledge Graph Completion
Subspace Clustering with Feature Grouping for Categorical Data
Learning Graph Neural Networks on Feature-Missing Graphs
Dealing with Over-reliance on Background Graph for Few-shot Knowledge Graph Completion
Kernel-based feature extraction for time series clustering
Cluster Robust Inference for embedding-based Knowledge Graph Completion
Community-enhanced Contrastive Siamese networks for Graph Representation Learning
Distant Supervision Relation Extraction with Improved PCNN and Multi-level Attention
Enhancing Adversarial Robustness via Anomaly-aware Adversarial Training
An Improved Cross-Validated Adversarial Validation Method
EACCNet: Enhanced Auto-Cross Correlation Network for Few-Shot Classification
Joint Label-Structure Estimation from Multifaceted Graph Data
Dual Channel Knowledge Graph Embedding with Ontology Guided Data Augmentation
Multi-Dimensional Graph Rule Learner
MixUNet: A Hybrid Retinal Vessels Segmentation Model Combining The Latest CNN and MLPs
Robust Few-shot Graph Anomaly Detection via Graph Coarsening
An Evaluation Metric for Prediction Stability with Imprecise Data
Reducing The Teacher-Student Gap Via Elastic Student.