Neural Information Processing : 31st International Conference, ICONIP 2024, Auckland, New Zealand, December 2–6, 2024, Proceedings, Part II / edited by Mufti Mahmud, Maryam Doborjeh, Kevin Wong, Andrew Chi Sing Leung, Zohreh Doborjeh, M. Tanveer.

Format:

Book

Author/Creator:

Mahmud, Mufti.

Contributor:

Doborjeh, Maryam.

Huang, Dejiang.

Leung, Andrew Chi Sing.

Doborjeh, Zohreh.

Tanveer, M.

Series:

Lecture Notes in Computer Science, 1611-3349 ; 15287

Language:

English

Subjects (All):

Pattern recognition systems.

Data mining.

Machine learning.

Automated Pattern Recognition.

Data Mining and Knowledge Discovery.

Machine Learning.

Local Subjects:

Automated Pattern Recognition.

Data Mining and Knowledge Discovery.

Machine Learning.

Physical Description:

1 online resource (772 pages)

Edition:

1st ed. 2025.

Place of Publication:

Singapore : Springer Nature Singapore : Imprint: Springer, 2025.

Summary:

The eleven-volume set LNCS 15286-15296 constitutes the refereed proceedings of the 31st International Conference on Neural Information Processing, ICONIP 2024, held in Auckland, New Zealand, in December 2024. The 318 regular papers presented in the proceedings set were carefully reviewed and selected from 1301 submissions. They focus on four main areas, namely: theory and algorithms; cognitive neurosciences; human-centered computing; and applications.

Contents:

Network structure and recurrent dynamics achieved by maximizing information transfer and minimizing maintenance costs of the network

Outlier-Robust Range-Based Method for Estimating the Location and Velocity of a Moving Source Using Lagrange Programming Neural Network

Spatial Analysis Techniques in Recognition and Localization of Mouse Neuronal Activity

ScaleMixer: A Multi-Scale MLP-Mixer Model for Long-Term Time Series Forecasting

Application of Pseudometric Functions in Clustering and a Novel Similarity Measure Based on Path Information Discrepancy

USAM-Net: A U-Net based network for improved stereo correspondence and scene depth estimation using features from a pre-trained image segmentation network

TaW-PeRCNN:Time-adaptive Weights Physics-encoded Recurrent Convolutional Neural Network for Solving Partial Differential Equations

An Explainable Error Detection Approach for Machine Learning

T-GET3D: A Generative Model of High-Quality 3D Textured Shapes Guided by Texts

Conformal Adversarial Generative Ensemble

Virtual Command Allocation: Enhancing Hexapod Robot Locomotion through Goal-Conditioned Reinforcement Learning

Adaptive Retrieval-based Gradient Planning for Offine Multi-context Model-based Optimization

RBHAR: Role-Based Heterogeneous Action Representation in Multi-Agent Reinforcement Learning

Deep mixtures of variational autoencoders model for representation learning and clustering tasks

TempoKGAT: A Novel Graph Attention Network Approach for Temporal Graph Analysis

Direct Correlational Spike-Timing-Dependent Plasticity Learning Applied to Classification Tasks

Wave-RVFL: A Randomized Neural Network Based on Wave Loss Function

Dual Cross Fusion Deep-unfolding Transformer for Hyperspectral Image Reconstruction

A weight averaging neural network for semi-supervised data stream learning

obust Noise Tolerant Algorithm for Randomized Neural Network

Tackling Periodic Distribution Shifts in Federated Learning with Half-cycle Knowledge Distillation

Multi-Scale Attention Convolutional Network and Reinforcement Learning for Flexible Job Shop Scheduling

Temporal State Prediction and Sequence Recovery for Multi-Agent Reinforcement Learning

Data Augmentation with Variational Autoencoder for Imbalanced Dataset

Performance Analysis of Quantum-Enhanced Kernel Classifiers Based on Feature Maps: A Case Study on EEG-BCI Data

Certified Patch Defense via Dual Mask-Preservation Prediction

Proximal Point Method for Online Saddle Point Problem

Fast Preserving Local Distances and Topology in Auto-Encoders

Neural Collapse Inspired Regularization for Deep Graph Neural Networks.

Notes:

Description based on publisher supplied metadata and other sources.

ISBN:

981-9665-79-5

OCLC:

1524423231