Hyebin Song

Assistant Professor of Statistics

Hyebin Song

Huck Affiliations

Links

Publication Tags

Variable Selection High Dimensional Learning Proteins Statistical Inference Labels Class Estimator Maximum Likelihood Estimation Testing Demonstrate Minimax Simulation Logistics Selection Bias Observation Generalized Linear Model Quantify Optimization Machine Learning Logistic Regression Asymptotic Variance Expectation Maximization Algorithm Sparsity Stationary Point

Most Recent Papers

Inferring Protein Sequence-Function Relationships with Large-Scale Positive-Unlabeled Learning

Hyebin Song, Bennett J. Bremer, Emily C. Hinds, Garvesh Raskutti, Philip A. Romero, 2021, Cell Systems on p. 92-101.e8

Convex and non-convex approaches for statistical inference with class-conditional noisy labels

Hyebin Song, Ran Dai, Garvesh Raskutti, Rina Foygel Barber, 2020, Journal of Machine Learning Research

Graph-Based Regularization for Regression Problems with Alignment and Highly Correlated Designs

Yuan Li, Benjamin Mark, Garvesh Raskutti, Rebecca Willett, Hyebin Song, David Neiman, 2020, SIAM J. Math. Data Sci. on p. 480--504

The bias of isotonic regression

Ran Dai, Hyebin Song, Rina Barber, Garvesh Raskutti, 2020, Electronic Journal of Statistics on p. 801-834

PUlasso

Hyebin Song, Garvesh Raskutti, 2020, Journal of the American Statistical Association on p. 334-347

PUlasso: High-Dimensional Variable Selection With Presence-Only Data

Hyebin Song, Garvesh Raskutti, 2019, Journal of the American Statistical Association on p. 334-347

Most-Cited Papers

PUlasso

Hyebin Song, Garvesh Raskutti, 2020, Journal of the American Statistical Association on p. 334-347

Convex and non-convex approaches for statistical inference with class-conditional noisy labels

Hyebin Song, Ran Dai, Garvesh Raskutti, Rina Foygel Barber, 2020, Journal of Machine Learning Research

Inferring Protein Sequence-Function Relationships with Large-Scale Positive-Unlabeled Learning

Hyebin Song, Bennett J. Bremer, Emily C. Hinds, Garvesh Raskutti, Philip A. Romero, 2021, Cell Systems on p. 92-101.e8

Graph-Based Regularization for Regression Problems with Alignment and Highly Correlated Designs

Yuan Li, Benjamin Mark, Garvesh Raskutti, Rebecca Willett, Hyebin Song, David Neiman, 2020, SIAM J. Math. Data Sci. on p. 480--504

The bias of isotonic regression

Ran Dai, Hyebin Song, Rina Barber, Garvesh Raskutti, 2020, Electronic Journal of Statistics on p. 801-834

PUlasso: High-Dimensional Variable Selection With Presence-Only Data

Hyebin Song, Garvesh Raskutti, 2019, Journal of the American Statistical Association on p. 334-347