(The following topics include but are not limited to)
Track 1: Neural Network Theory and Architecture
Deep Neural Network
Convolutional Neural Network (CNN)
Generative Adversarial Network (GAN)
Recurrent Neural Network (RNN)
Neural Network Structure and Topology Design
Neural Symbolic Hybrid Model
Interpretability and Visualization of Neural Networks
Pulse Neural Network and Neuromorphic Computing
Graph Neural Network
Transformer Architecture and Attention Mechanism
Autoencoder and Generative Model
Neural Network Compression and Pruning
Robustness and Defense against Adversarial Attacks of Neural Networks
Analysis and Research of Neural Networks in Fields such as Medicine, Finance, and Energy
Track 2: Machine Learning Algorithms and Methods
Supervised Learning, Unsupervised Learning, and Semi-supervised Learning
Reinforcement Learning and Deep Reinforcement Learning
Transfer Learning, Meta Learning, and Small Sample Learning
Self-supervised Learning and Contrastive Learning
Multi-task Learning and Multi-modal Learning
Ensemble Learning and Model Fusion Methods
Federated Learning and Distributed Machine Learning
Online Learning and Incremental Learning
Kernel Methods and Support Vector Machines
Clustering Analysis and Dimensionality Reduction Algorithms
Bayesian Learning and Probabilistic Graph Models
Causal Inference and Causal Machine Learning
Machine Learning Optimization Theory and Generalization Analysis
Interpretable Machine Learning and Model Transparency
Automatic Machine Learning and Neural Architecture Search
Evaluation and Benchmarking of Machine Learning Algorithms
Track 3: Algorithm Applications and Intelligent Systems
Computer Vision and Image Processing Applications
Natural Language Processing and Text Mining Applications
Speech Recognition and Audio Processing Applications
Recommendation Systems and Personalized Services
Knowledge Graphs and Semantic Computing
Intelligent Decision Support Systems and Business Intelligence
Intelligent Robots and Autonomous Systems
Embodied Intelligence and the Closed Loop of Perception-Decision-Control
Large Language Models and Generative AI Applications
Multimodal Learning and Cross-modal Intelligent Applications
Edge Intelligence and Embedded AI Deployment
Federated Learning and Privacy-Preserving Intelligent Computing
Interpretable AI and Trustworthy AI
...