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Robust importance sampling for error estimation in the context of optimal Bayesian transfer learning.

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第一作者： Omar,Maddouri

第一单位： Department of Electrical and Computer Engineering, Texas A&M University, College Station, TX 77843, USA.

作者： Omar,Maddouri ^[1] ; Xiaoning,Qian ^[2] ; Francis J,Alexander ^[3] ; Edward R,Dougherty ^[1] ; Byung-Jun,Yoon ^[2]

作者单位： Department of Electrical and Computer Engineering, Texas A&M University, College Station, TX 77843, USA. ^[1] Department of Electrical and Computer Engineering, Texas A&M University, College Station, TX 77843, USA.;Computational Science Initiative, Brookhaven National Laboratory, Upton, NY 11973, USA. ^[2] Computational Science Initiative, Brookhaven National Laboratory, Upton, NY 11973, USA. ^[3]

关键词 Bayesian error estimator OBTL classification error estimation importance sampling model uncertainty optimal Bayesian transfer learning transfer learning

DOI 10.1016/j.patter.2021.100428

PMID 35510184

发布时间 2024-08-27

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Patterns (New York, N.Y.)

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Robust importance sampling for error estimation in the context of optimal Bayesian transfer learning.

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Robust importance sampling for error estimation in the context of optimal Bayesian transfer learning.

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