Theory and Algorithms
Solving Partial Differential Equations using Point-based Neural Networks
Patch Mix Augmentation with Dual Encoders for Meta-Learning
Tacit Commitments Emergence in Multi-agent Reinforcement Learning
Saccade Direction Information Channel
Shared-Attribute Multi-Graph Clustering with Global Self-Attention
Mutual Diverse-Label Adversarial Training
Multi-Agent Hyper-Attention Policy Optimization
Filter Pruning via Similarity Clustering for Deep Convolutional Neural Networks
FPD: Feature Pyramid Knowledge Distillation
An effective ensemble model related to incremental learning in neural machine translation
Local-Global Semantic Fusion Single-shot Classification Method
Self-Reinforcing Feedback Domain Adaptation Channel
General Algorithm for Learning from Grouped Uncoupled Data and Pairwise Comparison Data
Additional Learning for Joint Probability Distribution Matching in BiGAN
Multi-View Self-Attention for Regression Domain Adaptation with Feature Selection
EigenGRF: Layer-Wise Eigen-Learning for Controllable Generative Radiance Fields
Partial Label learning with Gradually Induced Error-Correction Output Codes
HMC-PSO: A Hamiltonian Monte Carlo and Particle Swarm Optimization-based optimizer
Heterogeneous Graph Representation for Knowledge Tracing
Intuitionistic fuzzy universum support vector machine
Support vector machine based models with sparse auto-encoder based features for classification problem
Selectively increasing the diversity of GAN-generated samples
Cooperation and Competition: Flocking with Evolutionary Multi-Agent Reinforcement Learning
Differentiable Causal Discovery Under Heteroscedastic Noise
IDPL: Intra-subdomain adaptation adversarial learning segmentation method based on Dynamic Pseudo Labels
Adaptive Scaling for U-Net in Time Series Classification
Permutation Elementary Cellular Automata: Analysis and Application of Simple Examples
SSPR: A Skyline-Based Semantic Place Retrieval Method
Double Regularization-based RVFL and edRVFL Networks for Sparse-Dataset Classification
Adaptive Tabu Dropout for Regularization of Deep Neural Networks
Class-Incremental Learning with Multiscale Distillation for Weakly Supervised Temporal Action Localization
Nearest Neighbor Classifier with Margin Penalty for Active Learning
Factual Error Correction in Summarization with Retriever-Reader Pipeline
Context-adapted Multi-policy Ensemble Method for Generalization in Reinforcement Learning
Self-attention based multi-scale graph convolutional networks
Synesthesia Transformer with Contrastive Multimodal Learning
Context-based Point Generation Network for Point Cloud Completion
Temporal Neighborhood Change Centrality for Important Node Identification in Temporal Networks
DOM2R-Graph: A Web Attribute Extraction Architecture with Relation-aware Heterogeneous Graph Transformer
Sparse Linear Capsules for Matrix Factorization-based Collaborative Filtering
PromptFusion: a Low-cost Prompt-based Task Composition for Multi-task Learning
A fast and efficient algorithm for filtering the training dataset
Entropy-minimization Mean Teacher for Source-Free Domain Adaptive Object Detection
IA-CL: A Deep Bidirectional Competitive Learning Method for Traveling Salesman Problem
Boosting Graph Convolutional Networks With Semi-Supervised Training
Auxiliary Network: Scalable and agile online learning for dynamic system with inconsistently available inputs
VAAC: V-value Attention Actor-Critic for Cooperative Multi-agent Reinforcement Learning
An Analytical Estimation of Spiking Neural Networks Energy Efficiency
Correlation Based Semantic Transfer with Application to Domain Adaptation
Minimum Variance Embedded Intuitionistic Fuzzy Weighted Random Vector Functional Link Network
Neural Network Compression by Joint Sparsity Promotion and Redundancy Reduction.