Title Neural Information Processing 28th International Conference, ICONIP 2021, Sanur, Bali, Indonesia, December 8-12, 2021, Proceedings, Part II / edited by Teddy Mantoro, Minho Lee, Media Anugerah Ayu, Kok Wai Wong, Achmad Nizar Hidayanto

Edition 1st ed. 2021 EDITION 1 online resource Published Cham : Springer International Publishing : Imprint: Springer, 2021

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Series Theoretical Computer Science and General Issues, 2512-2029 ; 13109 Theoretical Computer Science and General Issues, 2512-2029 ; 13109 Contents 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 a Dual-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 Factorization Machines 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 Summary 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 In Springer Nature eBook Subject Pattern recognition systems. Machine learning. Education-Data processing Computer vision. Computer engineering. Computer networks  Form Electronic book Author Mantoro, Teddy. editor. Lee, Minho. editor. Ayu, Media Anugerah. editor. Wong, Kok Wai. editor. Hidayanto, Achmad Nizar. editor. SpringerLink (Online service) ISBN 9783030922702

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