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Neural Information Processing : 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
(Communications in Computer and Information Science. ISSN:18650937 ; 1791)

データ種別	電子ブック
版	1st ed. 2023.
出版者	(Singapore : Springer Nature Singapore : Imprint: Springer)
出版年	2023
大きさ	XXXV, 707 p. 203 illus., 176 illus. in color : online resource
著者標目	Tanveer, Mohammad editor Agarwal, Sonali editor Ozawa, Seiichi editor Ekbal, Asif editor Jatowt, Adam editor SpringerLink (Online service)

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URL	巻　次	配架場所	請求記号	登録番号	コメント	刷　年	状　態	利用注記	ISBN	予約	請求メモ
URL		射水-電子	007	EB0002678	Computer Scinece R0 2005-6,2022-3				9789819916399

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一般注記	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 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 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 HTTP:URL=https://doi.org/10.1007/978-981-99-1639-9
件　名	LCSH:Pattern recognition systems LCSH:Computer science LCSH:Artificial intelligence LCSH:Data mining LCSH:Data structures (Computer science) LCSH:Information theory FREE:Automated Pattern Recognition FREE:Theory and Algorithms for Application Domains FREE:Artificial Intelligence FREE:Data Mining and Knowledge Discovery FREE:Data Structures and Information Theory
分　類	LCC:Q337.5 LCC:TK7882.P3 DC23:006.4
書誌ID	EB00002066
ISBN	9789819916399