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Learning from Biased Data: A Semi-Parametric Approach
Patrice Bertail · Stephan Clémençon · Yannick Guyonvarch · Nathan NOIRY
Abstract:
We consider risk minimization problems where the (source) distribution PSPS of the training observations Z1,…,ZnZ1,…,Zn differs from the (target) distribution PTPT involved in the risk that one seeks to minimize. Under the natural assumption that PSPS dominates PTPT, \textit{i.e.} $P_T< \! \!
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