Neural Information Processing 30th International Conference, ICONIP 2023, Changsha, China, November 20–23, 2023, Proceedings, Part I

Theory and Algorithms.- Single Feedback Based Kernel Generalized Maximum Correntropy Adaptive Filtering Algorithm.- Application of Deep learning methods in the Diagnosis of Coronary Heart Disease based on Electronic Health Record.- Learning Adaptable Risk-Sensitive Policies to Coordinate in Multi-Agent General-Sum Games.- Traffic Data Recovery and Outlier Detection based on Non-Negative Matrix Factorization and Truncated-Quadratic Loss Function.- ADEQ: Adaptive Diversity Enhancement for Zero-shot Quantization.- ASTPSI: Allocating Spare Time and Planning Speed Interval for Intelligent Train Control of Sparse Reward.- Amortized variational inference via Nos\'e-Hoover Thermostat Hamiltonian Monte Carlo.- AM-RRT*: An Automatic Robot Motion Planning Algorithm based on RRT.- MS3DAAM: Multi-scale 3-D Analytic Attention Module for Convolutional Neural Networks.- Nonlinear Multiple-delay Feedback Based Kernel Least Mean Square Algorithm.- AGGDN: A Continuous Stochastic Predictive Model for Monitoring Sporadic Time Series on Graphs.- Attribution Guided Layerwise Knowledge Amalgamation from Graph Neural Networks.- Distributed Neurodynamic Approach for Optimal Allocation with Separable Resource Losses.- Multimodal Isotropic Neural Architecture with Patch Embedding.- Determination of local and global decision weights based on fuzzy modeling.- Binary Mother Tree Optimization Algorithm for 0/1 Knapsack Problem.- Distributed State Estimation for Multi-Agent Systems Under Consensus Control.- Integrated Design of Fully Distributed Adaptive State Estimation and Consensus Control for Multi-Agent Systems.- Computer Simulations of Applying Zhang Inequation Equivalency and Solver of Neurodynamics to Redundant Manipulators at Acceleration Level.- High-order control barrier function based robust collision avoidance formation tracking of constrained multi-agent systems.- Decision Support System based on MLP: Formula One (F1) Grand Prix Study Case.- Theoretical Analysis of Gradient-ZhangNeural Network for Time-Varying Equations and Improved Method for Linear Equations.- EdgeMA: Model Adaptation System for Real-Time Video Analytics on Edge Devices.- Mastering Complex Coordination through Attention-based Dynamic Graph.- SORA: Improving Multi-agent Cooperation with a Soft Role Assignment Mechanism.- Outer Synchronization for Multi-Derivative Coupled Complex Networks with and without External Disturbance.- A Distributed Projection-based Algorithm with Local Estimators for Optimal Formation of Multi-robot System.- A Stochastic Gradient-based Projection Algorithm for Distributed Constrained Optimization.- FalconNet: Factorization for the Light-weight ConvNets.- An Interactive Evolutionary Algorithm for Ceramic Formula Design.- Using Less But Important Information for Feature Distillation.- Efficient Mobile Robot Navigation Based on Federated Learning and Three-way Decisions.- GCM-FL: A Novel Granular Computing Model in Federated Learning for Fault Diagnosis.- Adaptive loadfrequency control and optimization based on TD3 algorithm and linear active disturbance rejection control.- Theory-guided Convolutional Neural Network with an Enhanced Water Flow Optimizer.- An End-to-End Dense Connected Heterogeneous Graph Convolutional Neural Network.- Actor-Critic with variable time discretization via sustained actions.- Scalable Bayesian Tensor Ring Factorization for Multiway Data Analysis.- Predefined-Time Event-Triggered Consensus for Nonlinear Multi-Agent Systems with Uncertain Parameter.- Cascaded fuzzy PID control for quadrotor UAVs based on RBF neural networks.- Generalizing Graph Network Models for the Traveling Salesman Problem with Lin-Kernighan-Helsgaun Heuristics.- Communication-Efficient Distributed Minimax Optimization via Markov Compression.- Multi-Level Augmentation Boosts Hybrid CNN-Transformer Model for Semi-Supervised Cardiac MRI Segmentation.- Wasserstein Diversity-Enriched Regularizer for Hierarchical Reinforcement Learning.- An Adaptive Detector for Few Shot Object Detection.