Computationally Efficient Methods for Invariant Feature Selection with Sparsity
Published in UAI, 2025
Invariant Risk Minimization (IRM) (Arjovsky et al., 2020) proposes an optimization scheme that uses causal features to improve generalization. However, in most realizations, it does not have an explicit feature selection strategy.
Recommended citation: Du, J., & Banerjee, A. (2025). Computationally Efficient Methods for Invariant Feature Selection with Sparsity. http://janezdu.github.io/files/uai2025.pdf