LEADER 07891nam 22007455 450 001 9910698651703321 005 20251113182942.0 010 $a9789819916399 010 $a9819916399 024 7 $a10.1007/978-981-99-1639-9 035 $a(CKB)5710000000117068 035 $a(DE-He213)978-981-99-1639-9 035 $a(MiAaPQ)EBC7238830 035 $a(Au-PeEL)EBL7238830 035 $a(PPN)269656332 035 $a(MiAaPQ)EBC7237223 035 $a(EXLCZ)995710000000117068 100 $a20230414d2023 u| 0 101 0 $aeng 135 $aurnn#008mamaa 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aNeural Information Processing $e29th International Conference, ICONIP 2022, Virtual Event, November 22?26, 2022, Proceedings, Part IV /$fedited by Mohammad Tanveer, Sonali Agarwal, Seiichi Ozawa, Asif Ekbal, Adam Jatowt 205 $a1st ed. 2023. 210 1$aSingapore :$cSpringer Nature Singapore :$cImprint: Springer,$d2023. 215 $a1 online resource (XXXV, 707 p. 203 illus., 176 illus. in color.) 225 1 $aCommunications in Computer and Information Science,$x1865-0937 ;$v1791 311 08$a9789819916382 311 08$a9819916380 320 $aIncludes bibliographical references and index. 327 $aTheory 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 andSyntactic 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. 330 $aThe four-volume set CCIS 1791, 1792, 1793 and 1794 constitutes the refereed proceedings of the 29th International Conference on Neural Information Processing, ICONIP 2022, held as a virtual event, November 22?26, 2022. The 213 papers presented in the proceedings set were carefully reviewed and selected from 810 submissions. They were organized in topical sections as follows: Theory and Algorithms; Cognitive Neurosciences; Human Centered Computing; and Applications. The ICONIP conference aims to provide a leading international forum for researchers, scientists, and industry professionals who are working in neuroscience, neural networks, deep learning, and related fields to share their new ideas, progress, and achievements. 410 0$aCommunications in Computer and Information Science,$x1865-0937 ;$v1791 606 $aPattern recognition systems 606 $aComputer science 606 $aArtificial intelligence 606 $aData mining 606 $aData structures (Computer science) 606 $aInformation theory 606 $aAutomated Pattern Recognition 606 $aTheory and Algorithms for Application Domains 606 $aArtificial Intelligence 606 $aData Mining and Knowledge Discovery 606 $aData Structures and Information Theory 615 0$aPattern recognition systems. 615 0$aComputer science. 615 0$aArtificial intelligence. 615 0$aData mining. 615 0$aData structures (Computer science). 615 0$aInformation theory. 615 14$aAutomated Pattern Recognition. 615 24$aTheory and Algorithms for Application Domains. 615 24$aArtificial Intelligence. 615 24$aData Mining and Knowledge Discovery. 615 24$aData Structures and Information Theory. 676 $a745.05 702 $aTanveer$b Mohammad 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910698651703321 996 $aNeural Information Processing$92554499 997 $aUNINA