Stephen Bradshaw

Semi-Supervised Learning under Spatially Biased Sampling

It is demonstrated that spatial non-stationarity contributes to performance loss independently of marginal mismatch and that models become increasingly overconfident outside the regions where labels are available, and introduced a kernel-weighted local divergence metric that provides a more stable estimate of spatial m...