(Including but not limited to the following topics)
Track 1: Artificial Intelligence
Machine Learning
Deep Learning Reinforcement Learning
Transfer learning
Federated learning
Generative artificial intelligence
Interpretable artificial intelligence
Multi-agent system
Edge intelligence
Human-machine intelligent interaction
Large language model
Self-supervised learning
Graph neural network Continuous learning
Intelligent optimization algorithms
Track 2: Algorithms
Algorithms and Data Structures
Quantum Algorithms and Computing
Biological Inspired and Evolutionary Algorithms
Random, Probabilistic and Approximate Algorithms
Optimization Based on Machine Learning
Algorithm Analysis, Approximate Algorithms
Computability Theory
Genetic Algorithms, Online Algorithms
Numerical Analysis
Sorting Algorithms
Algorithm Graph Theory and Combinatorics
Computational Geometry, Computing Techniques and Applications
Track 3: Data Analysis
Data Mining
Data Analysis Process and Improvement
Big Data Visualization Analysis Data analysis methods
Linear regression analysis
Statistical physics
Qualitative data analysis
High-frequency data analysis
Complex data analysis
Predictive analysis and simulation
Data analysis algorithms
Data analysis algorithms and systems
Data analysis scenarios and model applications
Big data machine learning
Big data platforms, technologies, models and methods
Big data tools and systems
Big data visualization analysis
Big data analysis and media ......