Neural Information Processing [E-Book] : 29th International Conference, ICONIP 2022, Virtual Event, November 22-26, 2022, Proceedings, Part IV /

Neural Information Processing [E-Book] : 29th International Conference, ICONIP 2022, Virtual Event, November 22-26, 2022, Proceedings, Part IV / edited by Mohammad Tanveer, Sonali Agarwal, Seiichi Ozawa, Asif Ekbal, Adam Jatowt.

The four-volume set CCIS 1791, 1792, 1793 and 1794 constitutes the refereed proceedings of the 29th International Conference on Neural Information Processing, ICONIP 2022, held as a virtual event, November 22-26, 2022. The 213 papers presented in the proceedings set were carefully reviewed and selec...

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Agarwal, Sonali, editor
Ekbal, Asif, editor / Jatowt, Adam, editor / Ozawa, Seiichi, editor / Tanveer, Mohammad, editor
1st edition 2023.
Singapore : Springer, 2023
XXXV, 707 pages 203 illustrations, 176 illustrations in color (online resource)
englisch
9789819916399
10.1007/978-981-99-1639-9
Communications in Computer and Information Science ; 1791
Artificial intelligence.
Computer science.
Data mining.
Data structures (Computer science).
Information theory.
Pattern recognition systems.



  • 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.