LEADER 05262nam 22006255 450 001 996664548003316 005 20250624130243.0 010 $a981-9665-79-5 024 7 $a10.1007/978-981-96-6579-2 035 $a(MiAaPQ)EBC32175380 035 $a(Au-PeEL)EBL32175380 035 $a(CKB)39445513000041 035 $a(DE-He213)978-981-96-6579-2 035 $a(EXLCZ)9939445513000041 100 $a20250624d2025 u| 0 101 0 $aeng 135 $aurcnu|||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aNeural Information Processing $e31st International Conference, ICONIP 2024, Auckland, New Zealand, December 2?6, 2024, Proceedings, Part II /$fedited by Mufti Mahmud, Maryam Doborjeh, Kevin Wong, Andrew Chi Sing Leung, Zohreh Doborjeh, M. Tanveer 205 $a1st ed. 2025. 210 1$aSingapore :$cSpringer Nature Singapore :$cImprint: Springer,$d2025. 215 $a1 online resource (772 pages) 225 1 $aLecture Notes in Computer Science,$x1611-3349 ;$v15287 311 08$a981-9665-78-7 327 $aNetwork 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. 330 $aThe eleven-volume set LNCS 15286-15296 constitutes the refereed proceedings of the 31st International Conference on Neural Information Processing, ICONIP 2024, held in Auckland, New Zealand, in December 2024. The 318 regular papers presented in the proceedings set were carefully reviewed and selected from 1301 submissions. They focus on four main areas, namely: theory and algorithms; cognitive neurosciences; human-centered computing; and applications. 410 0$aLecture Notes in Computer Science,$x1611-3349 ;$v15287 606 $aPattern recognition systems 606 $aData mining 606 $aMachine learning 606 $aAutomated Pattern Recognition 606 $aData Mining and Knowledge Discovery 606 $aMachine Learning 615 0$aPattern recognition systems. 615 0$aData mining. 615 0$aMachine learning. 615 14$aAutomated Pattern Recognition. 615 24$aData Mining and Knowledge Discovery. 615 24$aMachine Learning. 676 $a006.4 700 $aMahmud$b Mufti$01361230 701 $aDoborjeh$b Maryam$01827591 701 $aHuang$b Dejiang$01884775 701 $aLeung$b Andrew Chi Sing$01827593 701 $aDoborjeh$b Zohreh$01827594 701 $aTanveer$b M$01827595 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a996664548003316 996 $aNeural Information Processing$94519337 997 $aUNISA