E-grāmata: Neural Information Processing: 29th International Conference, ICONIP 2022, Virtual Event, November 22-26, 2022, Proceedings, Part I

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.