📚︎Track 1: Machine Learning Theory and Core Algorithms

• Deep Learning and Neural Network Architectures

• Reinforcement Learning and Decision Optimization

• Transfer Learning, Meta-Learning and Few-Shot Learning

• Self-Supervised and Contrastive Learning

• Federated Learning and Privacy-Preserving Machine Learning

• Graph Neural Networks and Graph Learning

• Explainable and Trustworthy Machine Learning

• Causal Inference and Causal Machine Learning

• Model Compression, Efficient Training and Inference

📚︎Track 2: Large Models and Generative AI

• Pre-training and Fine-tuning of Large Language Models

• Multimodal Foundation Models and Cross-Modal Learning

• Diffusion Models and Generative Adversarial Networks

• Retrieval-Augmented Generation and Knowledge Enhancement

• AI Agents and Tool Learning

• Prompt Engineering and In-Context Learning

• Alignment, Safety and Evaluation of Large Models

• Domain-Specific Large Models and Industry Applications

📚︎Track 3: Data Analysis, Mining and Data Intelligence

• Big Data Analytics and Distributed Computing

• Data Mining and Knowledge Discovery

• Time Series Analysis and Forecasting

• Anomaly Detection and Risk Identification

• Recommender Systems and User Behavior Analysis

• Data Governance, Data Quality and Data Cleaning

• Knowledge Graphs and Semantic Data Analysis

• Data Visualization and Visual Analytics

• Streaming Data and Real-Time Analytics

  
  

📚︎Track 4: Interdisciplinary Applications and Industry Practices

• Intelligent Healthcare and Bioinformatics

• FinTech and Intelligent Risk Control

• Intelligent Manufacturing and Industrial Big Data

• Smart Cities and Intelligent Transportation

• Computer Vision and Remote Sensing Image Analysis

• Natural Language Processing and Text Analysis

• Energy, Climate and Environmental Data Intelligence

• Educational Data Mining and Learning Analytics

• AI for Science

All accepted full papers will be published in the conference proceedings and will be submitted to EI Compendex / Scopus  for indexing.

Note: All submitted articles should report original research results, experimental or theoretical, not previously published or under consideration for publication elsewhere. Articles submitted to the conference should meet these criteria. We firmly believe that ethical conduct is the most essential virtue of academics. Hence, any act of plagiarism or other misconduct is totally unacceptable and cannot be tolerated.

Nico Bu

(Conference Secretary)

Tel: +86-17760758061 (WeChat)

E-Mail: contact_cmlda@163.com