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

Format:

Book

Contributor:

Tanveer, Mohammad, editor.

Series:

Lecture Notes in Computer Science, 1611-3349 ; 13623

Language:

English

Subjects (All):

Pattern recognition systems.

Data mining.

Machine learning.

Social sciences--Data processing.

Social sciences.

Automated Pattern Recognition.

Data Mining and Knowledge Discovery.

Machine Learning.

Computer Application in Social and Behavioral Sciences.

Local Subjects:

Automated Pattern Recognition.

Data Mining and Knowledge Discovery.

Machine Learning.

Computer Application in Social and Behavioral Sciences.

Physical Description:

1 online resource (660 pages)

Edition:

1st ed. 2023.

Place of Publication:

Cham : Springer International Publishing : Imprint: Springer, 2023.

Summary:

The three-volume set LNCS 13623, 13624, and 13625 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 146 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.

Contents:

Theory and Algorithms

Solving Partial Differential Equations using Point-based Neural Networks

Patch Mix Augmentation with Dual Encoders for Meta-Learning

Tacit Commitments Emergence in Multi-agent Reinforcement Learning

Saccade Direction Information Channel

Shared-Attribute Multi-Graph Clustering with Global Self-Attention

Mutual Diverse-Label Adversarial Training

Multi-Agent Hyper-Attention Policy Optimization

Filter Pruning via Similarity Clustering for Deep Convolutional Neural Networks

FPD: Feature Pyramid Knowledge Distillation

An effective ensemble model related to incremental learning in neural machine translation

Local-Global Semantic Fusion Single-shot Classification Method

Self-Reinforcing Feedback Domain Adaptation Channel

General Algorithm for Learning from Grouped Uncoupled Data and Pairwise Comparison Data

Additional Learning for Joint Probability Distribution Matching in BiGAN

Multi-View Self-Attention for Regression Domain Adaptation with Feature Selection

EigenGRF: Layer-Wise Eigen-Learning for Controllable Generative Radiance Fields

Partial Label learning with Gradually Induced Error-Correction Output Codes

HMC-PSO: A Hamiltonian Monte Carlo and Particle Swarm Optimization-based optimizer

Heterogeneous Graph Representation for Knowledge Tracing

Intuitionistic fuzzy universum support vector machine

Support vector machine based models with sparse auto-encoder based features for classification problem

Selectively increasing the diversity of GAN-generated samples

Cooperation and Competition: Flocking with Evolutionary Multi-Agent Reinforcement Learning

Differentiable Causal Discovery Under Heteroscedastic Noise

IDPL: Intra-subdomain adaptation adversarial learning segmentation method based on Dynamic Pseudo Labels

Adaptive Scaling for U-Net in Time Series Classification

Permutation Elementary Cellular Automata: Analysis and Application of Simple Examples

SSPR: A Skyline-Based Semantic Place Retrieval Method

Double Regularization-based RVFL and edRVFL Networks for Sparse-Dataset Classification

Adaptive Tabu Dropout for Regularization of Deep Neural Networks

Class-Incremental Learning with Multiscale Distillation for Weakly Supervised Temporal Action Localization

Nearest Neighbor Classifier with Margin Penalty for Active Learning

Factual Error Correction in Summarization with Retriever-Reader Pipeline

Context-adapted Multi-policy Ensemble Method for Generalization in Reinforcement Learning

Self-attention based multi-scale graph convolutional networks

Synesthesia Transformer with Contrastive Multimodal Learning

Context-based Point Generation Network for Point Cloud Completion

Temporal Neighborhood Change Centrality for Important Node Identification in Temporal Networks

DOM2R-Graph: A Web Attribute Extraction Architecture with Relation-aware Heterogeneous Graph Transformer

Sparse Linear Capsules for Matrix Factorization-based Collaborative Filtering

PromptFusion: a Low-cost Prompt-based Task Composition for Multi-task Learning

A fast and efficient algorithm for filtering the training dataset

Entropy-minimization Mean Teacher for Source-Free Domain Adaptive Object Detection

IA-CL: A Deep Bidirectional Competitive Learning Method for Traveling Salesman Problem

Boosting Graph Convolutional Networks With Semi-Supervised Training

Auxiliary Network: Scalable and agile online learning for dynamic system with inconsistently available inputs

VAAC: V-value Attention Actor-Critic for Cooperative Multi-agent Reinforcement Learning

An Analytical Estimation of Spiking Neural Networks Energy Efficiency

Correlation Based Semantic Transfer with Application to Domain Adaptation

Minimum Variance Embedded Intuitionistic Fuzzy Weighted Random Vector Functional Link Network

Neural Network Compression by Joint Sparsity Promotion and Redundancy Reduction.

Notes:

Includes bibliographical references and index.

Other Format:

Print version: Tanveer, Mohammad Neural Information Processing

ISBN:

9783031301056

OCLC:

1376446116