2 papers
cs.LG2023
Beta quantile regression for robust estimation of uncertainty in the presence of outliers
Haleh Akrami, Omar Zamzam, Anand Joshi +2
Quantile Regression (QR) can be used to estimate aleatoric uncertainty in deep neural networks and can generate prediction intervals. Quantifying uncertainty is particularly import…
cs.LG2023
Improved Differentially Private Regression via Gradient Boosting
Shuai Tang, Sergul Aydore, Michael Kearns +5
We revisit the problem of differentially private squared error linear regression. We observe that existing state-of-the-art methods are sensitive to the choice of hyperparameters -…