Neural Information Processing: 30th International Conference, ICONIP 2023, Changsha, China, November 2023, 2023, Proceedings, Part I 1st ed. 2024 [Pehme köide]

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.