(The following topics include but are not limited to)
Track 1: Core Methods of Machine Learning and Artificial Intelligence
New theories of supervised, semi-supervised, self-supervised and unsupervised learning
Deep learning architectures and their optimization
Reinforcement learning and deep reinforcement learning
Transfer learning, federated learning and continuous learning
Computational intelligence methods such as neural networks, fuzzy systems and evolutionary computing
Generative artificial intelligence
Interpretable artificial intelligence and trustworthy machine learning
Knowledge representation and reasoning, symbolic neural processing methods
Multi-agent systems and collaborative computing
Distributed and decentralized machine learning algorithms
Quantum machine learning and quantum AI
Artificial intelligence ethics, security and privacy protection
Track 2: Intelligent Information Processing and Data Science
Big data analysis and data mining
Information retrieval and recommendation systems
Knowledge graphs, semantic web and ontology modeling
Multimodal data fusion and intelligent processing
Computer vision and image/video processing
Pattern recognition and image understanding
Speech recognition, synthesis and audio processing
Natural language processing and computational linguistics
Cross-language processing and machine translation
Large language models and pre-trained language models
Data visualization and visual analysis
Biomedical signal and image analysis
Track 3: Intelligent Systems, Applications and Emerging Directions
Human-computer interaction and intelligent interfaces
Internet of Things and cyber-physical systems
Cloud computing, edge computing and distributed information systems
Intelligent decision support systems and expert systems
Intelligent robots, autonomous systems and autonomous driving
Smart healthcare, health informatics and precision medicine
Smart cities and environmental intelligent modeling
Cybersecurity, information privacy and trust mechanisms
Business intelligence and industrial applications
AI for Science (scientific intelligence)
Emerging applications and interdisciplinary cross-connections of intelligent information processing
...