An Empirical Investigation of Domain Generalization with Empirical Risk Minimizers (Appendix)

See table 1 for the results. We next perform regression in the Joint setting (Sec.5.3, main paper) where we fit a regression model across all environments, with 5 features instead of 2 reported in the main We find that it is possible to get an Spearman's We considered a set of 40 metrics overall and report only a small subset of them in the main paper. In table 2 we provide detailed results of all the measures we study. Figure 1 provides details of the canonicalization performed on each of the measures as explained in the main paper. In particular, (Ben-David et al., 2007) prove We also develop measures based on follow-up theoretical work in (Ben-David et al., 2010) on divergence measures using the symmetric difference hypothesis space. Here we summarize a result from (Ben-David et al., 2010), This canonicalization is used to report the results in Sec. 5 H: Z P (Y), we follow the steps in algorithm 1. Algorithm 1 Computing H -divergence measure As explained in the main paper, this divergence measure was proposed in (Ben-David et al., 2010).