arXiv:2410.19077
공식 코드 · Papers with Code
Target Strangeness: A Novel Conformal Prediction Difficulty Estimator
원문 초록
This paper introduces Target Strangeness, a novel difficulty estimator for conformal prediction (CP) that offers an alternative approach for normalizing prediction intervals (PIs). By assessing how atypical a prediction is within the context of its nearest neighbours' target distribution, Target Strangeness can surpass the current state-of-the-art performance. This novel difficulty estimator is evaluated against others in the context of several conformal regression experiments.
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Enhancing Adversarial Robustness with Conformal Prediction: A Framework for Guaranteed Model Reliability
Nearness of Neighbors Attention for Regression in Supervised Finetuning
Efficient Robust Conformal Prediction via Lipschitz-Bounded Networks
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