Poster
Learning from Biased Data: A Semi-Parametric Approach
Patrice Bertail · Stephan Clémençon · Yannick Guyonvarch · Nathan NOIRY
Keywords: [ Algorithms -> Clustering; Applications -> Hardware and Systems; Applications ] [ Privacy, Anonymity, and Security ] [ Theory ] [ Fairness, Accountability, and Transparency ]
Abstract:
We consider risk minimization problems where the (source) distribution $P_S$ of the training observations $Z_1, \ldots, Z_n$ differs from the (target) distribution $P_T$ involved in the risk that one seeks to minimize. Under the natural assumption that $P_S$ dominates $P_T$, \textit{i.e.} $P_T< \! \!
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