(Including but not limited to the following topics)
Track 1: Data Mining
Network mining, data stream mining
Parallel and distributed algorithms
Graph and subgraph mining
Large-scale data mining methods
Text, video and multimedia data mining
Scalable data preprocessing
High-performance data mining algorithms
Data security and privacy
E-commerce data mining systems
Big data analysis
Knowledge discovery, pattern recognition
Time series analysis
Data visualization
Privacy-preserving mining
Automated feature engineering
Data stream mining
Track 2: Machine Learning
Innovations in deep learning model architectures
Small sample learning and meta-learning methods
Self-supervised and contrastive learning algorithms
Breakthroughs in generative artificial intelligence theory
Reinforcement learning and decision optimization
Federated learning and distributed machine learning
Explainable machine learning methods
Machine learning adversarial attacks and robustness
Neuro-symbolic fusion learning
Open-source machine learning frameworks
Track 3: Intelligent Decision-making
Intelligent planning and scheduling
Reinforcement learning and decision-making
Multi-agent decision-making and game theory
Swarm intelligence and cluster decision-making
Uncertainty reasoning and robust decision-making
Explainable and trustworthy decision-making (XAI)
Knowledge-driven and hybrid decision-making
Online learning and real-time decision-making
Human-machine collaborative decision-making
Risk-aware decision-making, etc... .