Convex and Non-Convex Approaches for Statistical Inference with Class-Conditional Noisy Labels. - Hyebin Song; Ran Dai; Garvesh Raskutti; Rina Foygel Barber (J. Mach. Learn. Res., 2020)

Graph-Based Regularization for Regression Problems with Alignment and Highly Correlated Designs. - Yuan Li 006; Benjamin Mark; Garvesh Raskutti; Rebecca Willett; Hyebin Song; David Neiman (SIAM J. Math. Data Sci., 2020)

Prediction in the Presence of Response-Dependent Missing Labels. - Hyebin Song; Garvesh Raskutti; Rebecca Willett (SSP, 2021)

NURD: Negative-Unlabeled Learning for Online Datacenter Straggler Prediction. - Yi Ding 006; Avinash Rao; Hyebin Song; Rebecca Willett; Henry Hoffmann (MLSys, 2022)

Inferring protein fitness landscapes from laboratory evolution experiments. - Sameer D'Costa; Emily C. Hinds; Chase R. Freschlin; Hyebin Song; Philip A. Romero (PLoS Comput. Biol., 2023)

Multivariate Moment Least-Squares Variance Estimators for Reversible Markov Chains. - Hyebin Song; Stephen Berg (J. Comput. Graph. Stat., 2025)

Semi-Parametric Batched Global Multi-Armed Bandits with Covariates. - Sakshi Arya; Hyebin Song (CoRR, 2025)