1 citations · 1 across the 2 of their papers we have counts for
5 papers
Isotonic Conformal Prediction
Daniel Bensimon, Sean Xiang Yu, Eric D. Kolaczyk +1
A point prediction that is well calibrated on average can still be systematically biased conditional on its own value, undermining its use in downstream decision-making. We conside…
A Unified Framework for Regularized Estimating Equations via Fixed-Point and Variational Inequality Problems
Archer Y. Yang, Yue Zhao, Yi Lian +2
Many statistics problems are formulated within an estimating equation framework instead of a minimization framework. However, the regularized estimating equations (REE) have been m…
CAIRO: Decoupling Order from Scale in Regression
Harri Vanhems, Yue Zhao, Peng Shi +1
Standard regression methods typically optimize a single pointwise objective, such as mean squared error, which conflates the learning of ordering with the learning of scale. This c…
Why Self-Training Helps and Hurts: Denoising vs. Signal Forgetting
Mingqi Wu, Archer Y. Yang, Qiang Sun
Iterative self-training (self-distillation) repeatedly refits a model on pseudo-labels generated by its own predictions. We study this procedure in overparameterized linear regress…
Multivariate regression with missing response data for modelling regional DNA methylation QTLs
Shomoita Alam, Yixiao Zeng, Sasha Bernatsky +5
Identifying genetic regulators of DNA methylation (mQTLs) with multivariate models enhances statistical power, but is challenged by missing data from bisulfite sequencing. Standard…