(The following topics include but are not limited to)
Topic 1: Data Mining
Association Rules and Sequence Pattern Mining
Cluster analysis and anomaly detection
Classification and prediction models
Text and Web Mining
Spatiotemporal data mining
Graph Data and Social Network Mining
High dimensional and streaming data mining
Interpretability and Privacy of Data Mining
Topic 2: Machine Learning
Supervised and Unsupervised Learning
Semi supervised and weakly supervised learning
Reinforcement Learning and Multi Agent Learning
Ensemble Learning and Meta Learning
Transfer Learning and Domain Adaptation
Bayesian Learning and Probabilistic Graph Models
Online Learning and Active Learning
Machine Learning Theory
Topic 3: Deep Learning
Neural Network Architecture Design
Representation Learning and Feature Engineering
Generative Models and Adversarial Networks
Graph Neural Network
Attention mechanism and Transformer
Self supervision and contrastive learning
Deep Learning Optimization Algorithm
Deep Learning in Cross disciplinary Applications