Few-shot Multi-Task Learning of Linear Invariant Features with Meta Subspace Pursuit

ArXi:2409.02708v2 Announce Type: replace Data scarcity poses a serious threat to modern machine learning and artificial intelligence, as their practical success typically relies on the availability of big datasets. One effective strategy to mitigate the issue of insufficient data is to first harness information from other data sources possessing certain similarities in the study design stage, and then employ the multi-task or meta learning framework in the analysis stage.