Call for paper to PAKDD 2026

Theoretical Foundations: Generative AI, quantum ML, neuro-symbolic methods and reasoning, causal reasoning, non-IID learning, OOD generalization, representation learning, mathematical and statistical foundations, information theoretic approaches, optimization method, Theoretical foundations for fairness, trustworthy AI, safety, model explainability, and XAI
Learning Methods and Algorithms
Data Processing for Learning
Security, Privacy, Ethics, Information Integrity and Social Issues
Interdisciplinary Research on Data Science Applications