Domain Adaptation under Continuous Spurious Shift

TMLR Paper6500 Authors

Abstract: Recent advances in domain adaptation have shown promise in transferring knowledge across domains characterized by a continuous value or vector, such as varying patient ages, where “age” serves as a continuous index. However, these approaches often fail when spurious features shift continuously along with the domain index. This paper introduces the first method designed to withstand the continuous shifting of spurious features during domain adaptation. Our method enhances domain adaptation performance by aligning causally transportable encodings across continuously indexed domains. Theoretical analysis demonstrates that our approach more effectively ensures causal transportability across different domains. Empirical results, from both semi-synthetic and real-world medical datasets, indicate that our method outperforms state-of-the-art domain adaptation methods.

Submission Type: Regular submission (no more than 12 pages of main content)

Assigned Action Editor: ~Krikamol_Muandet1

Submission Number: 6500