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cs.LG2024★ 1 cited
How Does Unlabeled Data Provably Help Out-of-Distribution Detection?
Xuefeng Du, Zhen Fang, Ilias Diakonikolas +1
Using unlabeled data to regularize the machine learning models has demonstrated promise for improving safety and reliability in detecting out-of-distribution (OOD) data. Harnessing…
cs.LG2024
ConjNorm: Tractable Density Estimation for Out-of-Distribution Detection
Bo Peng, Yadan Luo, Yonggang Zhang +2
Post-hoc out-of-distribution (OOD) detection has garnered intensive attention in reliable machine learning. Many efforts have been dedicated to deriving score functions based on lo…