Neural Information Processing 28th International Conference, ICONIP 2021, Sanur, Bali, Indonesia, December 8–12, 2021, Proceedings, Part II

The four-volume proceedings LNCS 13108, 13109, 13110, and 13111 constitutes the proceedings of the 28th International Conference on Neural Information Processing, ICONIP 2021, which was held during December 8-12, 2021. The conference was planned to take place in Bali, Indonesia but changed to an online format due to the COVID-19 pandemic.

The total of 226 full papers presented in these proceedings was carefully reviewed and selected from 1093 submissions. The papers were organized in topical sections as follows:

Part I: Theory and algorithms;

Part II: Theory and algorithms; human centred computing; AI and cybersecurity;

Part III: Cognitive neurosciences; reliable, robust, and secure machine learning algorithms; theory and applications of natural computing paradigms; advances in deep and shallow machine learning algorithms for biomedical data and imaging; applications;  

Part IV: Applications.

Theory and Algorithms.- LSMVC: Low-rank Semi-supervised Multi-view Clustering for Special Equipment Safety Warning.- Single-Skeleton and Dual-Skeleton Hypergraph Convolution Neural Networks for Skeleton-Based Action Recognition.- Multi-Reservoir Echo State Network with Multiple-Size Input Time Slices for Nonlinear Time-Series Prediction.- Transformer with Prior Language Knowledge for Image Captioning.- Continual Learning with Laplace Operator based Node-Importance Dynamic Architecture Neural Network.- Improving generalization of reinforcement learning for multi-agent combating games.- Gradient Boosting Forest: A Two-Stage Ensemble Method Enabling Federated Learning of GBDTs.- Random Neural Graph Generation with Structure Evolution.- MatchMaker: Aspect-Based Sentiment Classification via Mutual Information.- PathSAGE: Spatial Graph Attention Neural Networks With Random Path Sampling.- Label Preserved Heterogeneous Network Embedding.- Spatio-Temporal Dynamic Multi-Graph Attention Network for Ride-hailing Demand Prediction.- An Implicit Learning Approach for Solving the Nurse Scheduling Problem.- Improving Goal-Oriented Visual Dialogue by Asking Fewer Questions.- Balance Between Performance and Robustness of Recurrent Neural Networks brought by Brain-inspired Constraints on Initial Structure.- Single-Image Smoker Detection by Human-Object Interaction with Post-Refinement.- A Lightweight Multi-scale Feature Fusion Network For Real-time Semantic Segmentation.- Multi-view Fractional Deep Canonical Correlation Analysis for Subspace Clustering.- Handling the Deviation from Isometry between Domains and Languages in Word Embeddings: Applications to Biomedical Text Translation.- Inference in Neural Networks Using Conditional Mean-Field Methods.- Associative Graphs for Fine-Grained Text Sentiment Analysis.- k-Winners-Take-All Ensemble Neural Network.- Performance Improvement of FORCE Learning for Chaotic Echo State Networks.- Generative Adversarial Domain Generalization via Cross-Task Feature Attention Learning for Prostate Segmentation.- Context-based Deep Learning Architecture with Optimal Integration Layer for Image Parsing.- Kernelized Transfer Feature Learning on Manifolds.- Data-Free Knowledge Distillation with Positive-Unlabeled Learning.- Manifold Discriminative Transfer Learning for Unsupervised Domain Adaptation.- Training-Free Multi-Objective Evolutionary Neural Architecture Search via Neural Tangent Kernel and Number of Linear Regions.- Neural Network Pruning via Genetic Wavelet Channel Search.- Binary Label-aware Transfer Learning  for Cross-domain Slot Filling.- Condition-Invariant Physical Adversarial Attacks via Pixel-wise Adversarial Learning.- Multiple Partitions Alignment with Adaptive Similarity Learning.- Recommending best course of treatment based on similarities of prognostic markers.- Generative Adversarial Negative Imitation Learning from Noisy Demonstrations.- Detecting Helmets on Motorcyclists by Deep Neural Networks with aDual-Detection Scheme.- Short-Long Correlation Based Graph Neural Networks for Residential Load Forecasting.- Disentangled Feature Network for Fine-Grained Recognition.- Large-Scale Topological Radar Localization Using Learned Descriptors.- Rethinking binary hyperparameters for deep transfer learning.- Human Centred Computing.- Hierarchical Features Integration and Attention Iteration Network for Juvenile Refractive Power Prediction.- Stress Recognition in Thermal Videos using Bi-Directional Long-Term Recurrent Convolutional Neural Networks.- StressNet: A Deep Neural Network based on Dynamic Dropout Layers for Stress Recognition.- Analyzing Vietnamese Legal Questions using Deep Neural Networks with Biaffine Classifiers.- BenAV: A Bengali Audio-Visual Corpus for Visual Speech Recognition.- Investigation of Different G2P Schemes for Speech Recognition in Sanskrit.- GRU with Level-Aware Attention for Rumor Early Detection in Social Networks.- Convolutional Feature-interacted FactorizationMachines for Sparse Contextual Prediction.- A Lightweight Multidimensional Self-Attention Network for Fine-grained Action Recognition.- Unsupervised Domain Adaptation with Self-selected Active Learning for Cross-domain OCT Image Segmentation.- Adaptive Graph Convolutional Network with Prior Knowledge for Action Recognition.- Self-Adaptive Graph Neural Networks for Personalized Sequential Recommendation.- Spitial-Temporal Attention Network with Multi-Similarity Loss for Fine-Grained Skeleton-Based Action Recognition.- SRGAT: Social Relational Graph Attention Network for Human Trajectory Prediction.- FSE: A powerful feature augmentation technique for classification task.- AI and Cybersecurity.- FHTC: Few-shot Hierarchical Text Classification in Financial Domain.- JStrack: Enriching Malicious JavaScript Detection Based on AST Graph Analysis and Attention Mechanism.