5 papers
Prediction-Powered Conditional Inference
Yang Sui, Jin Zhou, Hua Zhou +1
We study prediction-powered conditional inference in the setting where labeled data are scarce, unlabeled covariates are abundant, and a black-box machine-learning predictor is ava…
Multi-task Learning for Heterogeneous Multi-source Block-Wise Missing Data
Yang Sui, Qi Xu, Yang Bai +1
Multi-task learning (MTL) has emerged as an imperative machine learning tool to solve multiple learning tasks simultaneously and has been successfully applied to healthcare, market…
Multi-Task Learning with Covariate-Overlap Regularization
Yang Sui, Qi Xu, Yang Bai +1
Multi-task learning improves data efficiency by sharing information across related tasks, but indiscriminate sharing can be harmful when their covariate distributions and response…
Partially-shared Imaging Regression on Integrating Heterogeneous Brain-Cognition Associations across Alzheimer's Diagnoses
Yang Sui, Qi Xu, Ting Li +2
Alzheimer's Disease Neuroimaging Initiative (ADNI) diagnostic groups present strong heterogeneous associations among demographic, imaging, and cognitive data. We propose a novel PA…
Implicit Regularization in Over-Parameterized Support Vector Machine
Yang Sui, Xin He, Yang Bai
In this paper, we design a regularization-free algorithm for high-dimensional support vector machines (SVMs) by integrating over-parameterization with Nesterov's smoothing method,…