On efficiency of Learning Under Privileged Information

Research output: Chapter in Book/Report/Conference proceedingConference contribution


The paradigm of Learning Under Privileged Information (LUPI) was used in various prac- tical applications, including its combination with Conformal Prediction (CP) framework. In this note, we discuss possible sources and limitations of its efficiency. We try to argue that accuracy improvement coming from using privileged information is not occasional. For this goal, we consider some minimalistic models of LUPI where the contribution of the privileged information appears in its noise-free essence. Then, we discuss connection of LUPI paradigm and CP framework in relation with the models.
Original languageEnglish
Title of host publication11th Symposium on Conformal and Probabilistic Prediction with Applications
Place of PublicationBrighton, UK
PublisherProceedings of Machine Learning Research, 2022 Conformal and Probabilistic Prediction and Applications
Number of pages14
Publication statusPublished - 25 Aug 2022


  • Conformal prediction
  • privileged information
  • efficiency

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