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Neural Information Processing 29th International Conference, ICONIP 2022, Virtual Event, November 22-26, 2022, Proceedings, Part IV
Title
Neural Information Processing [electronic resource] : 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.
ISBN
9789819916399
Edition
1st ed. 2023.
Publication
Singapore : Springer Nature Singapore : Imprint: Springer, 2023.
Physical Description
1 online resource (XXXV, 707 p.) 203 illus., 176 illus. in color.
Local Notes
Access is available to the Yale community.
Access and use
Access restricted by licensing agreement.
Summary
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.
Variant and related titles
Springer ENIN.
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Format
Books / Online
Language
English
Added to Catalog
May 09, 2023
Series
Communications in Computer and Information Science, 1791
Contents
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.
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