研究人员开发了共识预测的新方法，这是一种用于量化机器学习模型不确定性的框架。一篇论文提出了概率伯努利预测集（BPS），它可以表达偶然性和认知不确定性，并为有效的可信集实现条件覆盖。另一种方法侧重于在再生核希尔伯特空间（RKHS）内有效地逼近完整的共识预测区域。此外，还引入了一个名为 RoBAS 的鲁棒贝叶斯辅助共识预测框架，该框架能够适应贝叶斯先验的可靠性，从而生成有效的预测集，尤其是在分布偏移的情况下。
AI
arXiv:2601.02998v2 Announce Type: replace-cross Abstract: In many fairness and distribution robustness problems, one has access to labeled data from multiple source distributions yet the test data may come from an arbitrary member or a mixture of them. We study the problem of con…
arXiv:2604.11305v3 Announce Type: replace-cross Abstract: Conformal selection (CS) uses calibration data to identify test inputs whose unobserved outcomes are likely to satisfy a pre-specified minimal quality requirement, while controlling the false discovery rate (FDR). Existing…
arXiv stat.ML
TIER_1English(EN)·Alireza Javanmardi, Soroush H. Zargarbashi, Santo M. A. R. Thies, Willem Waegeman, Aleksandar Bojchevski, Eyke H\"ullermeier·
arXiv:2505.19033v2 Announce Type: replace Abstract: Conformal prediction (CP) is a widely used frequentist framework to quantify uncertainty by constructing prediction sets with user-specified marginal coverage guarantees. In practice, CP is typically applied on top of probabilis…
arXiv:2601.13102v3 Announce Type: replace Abstract: Full conformal prediction is a framework that implicitly formulates distribution-free confidence prediction regions for a wide range of estimators. However, a classical limitation of the full conformal framework is the computati…
arXiv:2607.04236v1 Announce Type: new Abstract: Bayes-assisted conformal prediction combines the strengths of Bayesian modelling with exact, distribution-free frequentist coverage guarantees. Although conformal validity is preserved even when the Bayesian working model (BWM) is m…
Bayes-assisted conformal prediction combines the strengths of Bayesian modelling with exact, distribution-free frequentist coverage guarantees. Although conformal validity is preserved even when the Bayesian working model (BWM) is misspecified, the size of the resulting predictio…
Bayes-assisted conformal prediction combines the strengths of Bayesian modelling with exact, distribution-free frequentist coverage guarantees. Although conformal validity is preserved even when the Bayesian working model (BWM) is misspecified, the size of the resulting predictio…
