國立高雄大學圖資館 |

Neural information processing29th International Conference, ICONIP 2022, virtual event, November 22-26, 2022 : proceedings.Part IV /

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Neural information processingedited by Mohammad Tanveer ... [et al.].
其他題名:	29th International Conference, ICONIP 2022, virtual event, November 22-26, 2022 : proceedings.
其他題名:	ICONIP 2022
其他作者:	Tanveer, Mohammad.
團體作者:
出版者:	Singapore :Springer Nature Singapore :2023.
面頁冊數:	xxxv, 707 p. :ill., digital ;24 cm.
Contained By:	Springer Nature eBook
標題:	Neural computersCongresses.
電子資源:	https://doi.org/10.1007/978-981-99-1639-9
ISBN:	9789819916399$q(electronic bk.)

Neural information processing29th International Conference, ICONIP 2022, virtual event, November 22-26, 2022 : proceedings.Part IV /
Neural information processing29th International Conference, ICONIP 2022, virtual event, November 22-26, 2022 : proceedings.Part IV /[electronic resource] :ICONIP 2022edited by Mohammad Tanveer ... [et al.]. - Singapore :Springer Nature Singapore :2023. - xxxv, 707 p. :ill., digital ;24 cm. - Communications in computer and information science,17911865-0937 ;. - Communications in computer and information science ;229..

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.

ISBN: 9789819916399$q(electronic bk.)

Standard No.: 10.1007/978-981-99-1639-9doiSubjects--Topical Terms:

387160
Neural computers
--Congresses.

LC Class. No.: QA76.87

Dewey Class. No.: 006.32

Neural information processing29th International Conference, ICONIP 2022, virtual event, November 22-26, 2022 : proceedings.Part IV /
LDR:06440nmm a2200349 a 4500 001 642541
003 DE-He213
005 20230414085434.0
006 m d
007 cr nn 008maaau
008 231123s2023 si s 0 eng d
020 $a 9789819916399$q(electronic bk.)
020 $a 9789819916382$q(paper)
024 7 $a 10.1007/978-981-99-1639-9 $2 doi
035 $a 978-981-99-1639-9
040 $a GP $c GP
041 0 $a eng
050 4 $a QA76.87
072 7 $a UYQP $2 bicssc
072 7 $a COM016000 $2 bisacsh
072 7 $a UYQP $2 thema
082 0 4 $a 006.32 $2 23
090 $a QA76.87 $b .I17 2022
111 2 $n (3rd : $d 1998 : $c Amsterdam, Netherlands) $3 194767
245 1 0 $a Neural information processing $h [electronic resource] : $b 29th International Conference, ICONIP 2022, virtual event, November 22-26, 2022 : proceedings. $n Part IV / $c edited by Mohammad Tanveer ... [et al.].
246 3 $a ICONIP 2022
260 $a Singapore : $b Springer Nature Singapore : $b Imprint: Springer, $c 2023.
300 $a xxxv, 707 p. : $b ill., digital ; $c 24 cm.
490 1 $a Communications in computer and information science, $x 1865-0937 ; $v 1791
505 0 $a 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.
520 $a 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.
650 0 $a Neural computers $v Congresses. $3 387160
650 0 $a Neural networks (Computer science) $3 181982
650 1 4 $a Automated Pattern Recognition. $3 913155
650 2 4 $a Theory and Algorithms for Application Domains. $3 921479
650 2 4 $a Artificial Intelligence. $3 212515
650 2 4 $a Data Mining and Knowledge Discovery. $3 275288
650 2 4 $a Data Structures and Information Theory. $3 825714
700 1 $a Tanveer, Mohammad. $3 949888
710 2 $a SpringerLink (Online service) $3 273601
773 0 $t Springer Nature eBook
830 0 $a Communications in computer and information science ; $v 229. $3 547963
856 4 0 $u https://doi.org/10.1007/978-981-99-1639-9
950 $a Computer Science (SpringerNature-11645)