Theory and Algorithms
Knowledge Transfer from Situation Evaluation to Multi-agent Reinforcement Learning
Sequential three-way rules class-overlap under-sampling based on fuzzy hierarchical subspace for imbalanced data
Two-stage Multilayer Perceptron Hawkes Process
The Context Hierarchical Contrastive Learning for Time Series in Frequency Domain
Hawkes Process via Graph Contrastive Discriminant representation Learning and Transformer capturing long-term dependencies
A Temporal Consistency Enhancement Algorithm Based On Pixel Flicker Correction
Data representation and clustering with double low-rank constraints
RoMA: a Method for Neural Network Robustness Measurement and Assessment
Independent Relationship Detection for Real-Time Scene Graph Generation
A multi-label feature selection method based on feature graph with ridge regression and eigenvector centrality
O3GPT: A Guidance-Oriented Periodic Testing Framework with Online Learning, Online Testing, and Online Feedback
AFFSRN: Attention-Based Feature Fusion Super-Resolution Network
Temporal-Sequential Learning with Columnar-Structured Spiking Neural Networks
Graph Attention Transformer Network for Robust Visual Tracking
GCL-KGE:Graph Contrastive Learning for Knowledge Graph Embedding
Towards a Unified Benchmark for Reinforcement Learning in Sparse Reward Environments
Effect of Logistic Activation Function and Multiplicative Input Noise on DNN-kWTA model
A High-Speed SSVEP-Based Speller Using Continuous Spelling Method
AAT: Non-Local Networks for Sim-to-Real Adversarial Augmentation Transfer
Aggregating Intra-class and Inter-class information for Multi-label Text Classification
Fast estimation of multidimensional regression functions by the Parzen kernel-based method
ReGAE: Graph autoencoder based on recursive neural networks
Efficient Uncertainty Quantification for Under-constraint Prediction following Learning using MCMC
SMART: A Robustness Evaluation Framework for Neural Networks
Time-aware Quaternion Convolutional Network for Temporal Knowledge Graph Reasoning
SumBART - An improved BART model for abstractive text summarization
Saliency-Guided Learned Image Compression for Object Detection
Multi-Label Learning with Data Self-Augmentation
MnRec: A News Recommendation Fusion Model Combining Multi-granularity Information
Infinite Label Selection Method for Mutil-label Classification
Simultaneous Perturbation Method for Multi-Task Weight Optimization in One-Shot Meta-Learning
Searching for Textual Adversarial Examples with Learned Strategy
Multivariate Time Series Retrieval with Binary Coding from Transformer. -Learning TSP Combinatorial Search and Optimization with Heuristic Search
A Joint Learning Model for Open Set Recognition with Post-processing
Cross-Layer Fusion for Feature Distillation
MCHPT: A Weakly Supervise Based Merchant Pre-trained Model
Progressive Latent Replay for efficient Generative Rehearsal
Generalization Bounds for Set-to-Set Matching with Negative Sampling
ADA: An Attention-Based Data Augmentation Approach to Handle Imbalanced Textual Datasets
Countering the Anti-detection Adversarial Attacks
Evolving Temporal Knowledge Graphs by Iterative Spatio-Temporal Walks
Improving Knowledge Graph Embedding Using Dynamic Aggregation of Neighbor Information
Generative Generalized Zero-Shot Learning based on Auxiliary-Features
Learning Stable Representations with Progressive Autoencoder (PAE)
Effect of Image Down-sampling on Detection of Adversarial Examples
Boosting the Robustness of Neural Networks with M-PGD
StatMix: Data augmentation method that relies on image statistics in federated learning
Classification by Components Including Chow's Reject Option. -Community discovery algorithm based on improved deep sparse autoencoder
Fairly Constricted Multi-Objective Particle Swarm Optimization
Argument Classification with BERT plus Contextual, Structural and Syntactic Features as Text
Variance Reduction for Deep Q-Learning using Stochastic Recursive Gradient
Optimizing Knowledge Distillation Via Shallow Texture Knowledge Transfer
Unsupervised Domain Adaptation Supplemented with Generated Images
MAR2MIX: A Novel Model for Dynamic Problem in Multi-Agent Reinforcement Learning
Adversarial Training with Knowledge Distillation Considering Intermediate Representations in CNNs
Deep Contrastive Multi-view Subspace Clustering.