Conformal predictive distributions with kernels
This work addresses the integration of predictive distributions into machine learning, but it appears incremental as it reviews and combines existing ideas.
The paper reviews the history of predictive distributions and introduces two developments: integrating them into machine learning and combining them with kernel methods, though no specific results or numbers are provided.
This paper reviews the checkered history of predictive distributions in statistics and discusses two developments, one from recent literature and the other new. The first development is bringing predictive distributions into machine learning, whose early development was so deeply influenced by two remarkable groups at the Institute of Automation and Remote Control. The second development is combining predictive distributions with kernel methods, which were originated by one of those groups, including Emmanuel Braverman.