AI RESEARCH
On the Power of Source Screening for Learning Shared Feature Extractors
arXiv CS.LG
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ArXi:2602.16125v2 Announce Type: replace Learning with shared representation is widely recognized as an effective way to separate commonalities from heterogeneity across various heterogeneous sources. Most existing work includes all related data sources via simultaneously