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Learning from Biased Data: A Semi-Parametric Approach
Patrice Bertail · Stephan Clémençon · Yannick Guyonvarch · Nathan NOIRY

Wed Jul 21 07:20 AM -- 07:25 AM (PDT) @
in Learning Theory 6 »
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< \! \!
Keywords: Privacy, Anonymity, and Security · Fairness, Accountability, and Transparency · Theory · Algorithms -> Clustering; Applications -> Hardware and Systems; Applications

Author Information

Patrice Bertail (Université Paris Nanterre)
Stephan Clémençon (Télécom Paris)
Yannick Guyonvarch (Télécom Paris)
Nathan NOIRY (Telecom Paris)

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