(The following topics include but are not limited to)
Topic 1: Machine Learning
Deep learning, neural networks, reinforcement learning, transfer learning, federated learning, self supervised learning, small sample learning, meta learning, graph neural networks, generative adversarial networks, model compression and acceleration, knowledge distillation, interpretable machine learning, multimodal learning, edge intelligence, embedded learning, natural language processing, pattern recognition, predictive modeling, anomaly detection, recommendation systems, clustering algorithms, classification algorithms, regression analysis, feature extraction and selection, representation learning, metric learning
Topic 2: Artificial Intelligence
Deep learning applications, scenario reinforcement learning, AI urban traffic optimization, urban AI security and monitoring, intelligent government natural language processing, AI algorithm transparency, multimodal AI perception, AI emergency response models, generative AI intelligent services, urban federated learning practices
Theme 3: Modern Education
Learning models, lifelong education, collaborative learning, community building, educational technology, e-learning, service learning, blended learning, computer distance education, education (general), gamification in learning, personalized learning and curriculum design, computer applications in social and behavioral sciences, massive open online courses (MOOCs), leveraging e-learning to enhance teaching methods