1 citations · 1 across the 8 of their papers we have counts for
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Protected Test-Time Adaptation via Online Entropy Matching: A Betting Approach
Yarin Bar, Shalev Shaer, Yaniv Romano
We present a novel approach for test-time adaptation via online self-training, consisting of two components. First, we introduce a statistical framework that detects distribution s…
Robust Conformal Prediction Using Privileged Information
Shai Feldman, Yaniv Romano
We develop a method to generate prediction sets with a guaranteed coverage rate that is robust to corruptions in the training data, such as missing or noisy variables. Our approach…
Predictive Uncertainty Quantification with Missing Covariates
Margaux Zaffran, Julie Josse, Yaniv Romano +1
Predictive uncertainty quantification is crucial in decision-making problems. We investigate how to adequately quantify predictive uncertainty with missing covariates. A bottleneck…
Provably Robust Conformal Prediction with Improved Efficiency
Ge Yan, Yaniv Romano, Tsui-Wei Weng
Conformal prediction is a powerful tool to generate uncertainty sets with guaranteed coverage using any predictive model, under the assumption that the training and test data are i…