Neural Information Processing : 31st International Conference, ICONIP 2024, Auckland, New Zealand, December 2–6, 2024, Proceedings, Part I / 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 ; 15286

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 (701 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:

Defend from Scratch: A Diffusion-based Proactive Defense Method for Unauthorized Speech Synthesis

Transformers As Approximations of Solomonoff Induction

Interpreting Decision Transformer: Insights from Continuous Control Tasks

Flexible-order Feature-interaction for Mixed Continuous and Discrete Variables with Group-level Interpretability

Critical Feature Sifting and Dynamic Aggregation for Anomalous Audio Sequence Detection

Parallel Interpretation Network via Semantic Visual Probe and Counterfactual Verification

Real-Time Decentralized M2M Decision-Making via Deep Learning and Incremental Learning

Explainable Federated Stacking Models with Encrypted Gradients for Secure Kidney Medical Imaging Diagnosis

DDFGNN: Dual-dimensionality Fusion Graph Neural Network for Social Bot Detection

A Motif-based Graph Convolution Network for Stock Trend Prediction

VAGNN: Advancing the Generalization of Graph Neural Networks

TrajAngleNet: Transformer-based Trajectory Prediction through Multi-Task Learning with Angle Prediction

Correlation Disentangling and Spatio-Temporal Cooperative Optimizing Network for Temperature Prediction Revision

Hierarchical Adaptive Position Encoding-based Transformer for Point Cloud Analysis

In-context Learning for Temperature Field Reconstruction under Multiple Layouts

Loosely coupled oscillators as a correlate of behavioral control circuits within the central complex of the fruit fly

EL-LSTM: A Multivariate Time Series Forecasting Model Combining Spiking Neurons and Long Short-Term Memory Networks

A Two-Stage Network for Enhanced Intracranial Artery 3D Segmentation in TOF-MRA Volume

Independence Constrained Disentangled Representation Learning from pistemological Perspective

Utilizing Small and Large Spectral Radii for Appropriate Reservoir Computing Design

Noisy Deep Ensemble: Accelerating Deep Ensemble Learning via Noise Injection

LCNet: Lightning Hierarchical Convolution for Occupancy Flow Prediction

FedTS: Leveraging Teacher-Student Architecture in Federated Learning against Model Heterogeneity in Edge Computing Scenarios

Physics-informed antisymmetric recurrent neural networks for solving nonlinear partial differential equations

APS: An Adaptive Policy Switching Framework to Improve the Generalization of Branching

Efficient Pruning and Compression Techniques for Convolutional Neural Networks to Preserve Knowledge and Optimize Performance

Enhancing Convnets with Pruning and Symmetry-Based Filter Augmentation

Improved Approximation Algorithms for the Cumulative Vehicle Routing Problem.

Notes:

Description based on publisher supplied metadata and other sources.

ISBN:

981-9665-76-0

OCLC:

1528362625