Hyebin Song

Assistant Professor of Statistics

Hyebin Song

Huck Affiliations

Links

Publication Tags

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Labels Convergence Rate High Dimensional Learning Guarantee Term Dependent Class Coefficients Fires Variable Selection Single Index Model Proteins Statistical Inference Monotone Prediction Estimator Index Model Demonstrate Observation Testing Maximum Likelihood Estimation Minimax Model Link Function

Most Recent Publications

Inferring protein fitness landscapes from laboratory evolution experiments

Sameer D'Costa, Emily Hinds, Chase Freschlin, Hyebin Song, Philip Romero, PLOS Computational Biology on p. e1010956

Non-covalent Lasso Entanglements in Folded Proteins: Prevalence, Functional Implications, and Evolutionary Significance

Viraj Rana, Ian Sitarik, Justin Petucci, Yang Jiang, Hyebin Song, Edward P. O'Brien, 2024, Journal of Molecular Biology

EFFICIENT SHAPE-CONSTRAINED INFERENCE FOR THE AUTOCOVARIANCE SEQUENCE FROM A REVERSIBLE MARKOV CHAIN

Stephen Berg, hyebin song, 2023, Annals of Statistics on p. 2440-2470

Inferring protein fitness landscapes from laboratory evolution experiments

Sameer D’Costa, Emily C. Hinds, Chase R. Freschlin, Hyebin Song, Philip A. Romero, 2023, PLoS Computational Biology

Nurd: Negative-unlabeled learning for online datacenter straggler prediction

Yi Ding, Avinash Rao, Hyebin Song, Rebecca Willett, Henry Hoffmann, 2022, Proceedings of Machine Learning and Systems on p. 190--203

Convergence guarantee for the sparse monotone single index model<sup>∗</sup>

Ran Dai, Hyebin Song, Rina Foygel Barber, Garvesh Raskutti, 2022, Electronic Journal of Statistics on p. 4449-4496

Prediction in the Presence of Response-Dependent Missing Labels

Hyebin Song, Garvesh Raskutti, Rebecca Willett, 2021, on p. 451-455

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 journal on mathematics of data science on p. 480--504

Most-Cited 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

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

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 fitness landscapes from laboratory evolution experiments

Sameer D’Costa, Emily C. Hinds, Chase R. Freschlin, Hyebin Song, Philip A. Romero, 2023, PLoS Computational Biology

EFFICIENT SHAPE-CONSTRAINED INFERENCE FOR THE AUTOCOVARIANCE SEQUENCE FROM A REVERSIBLE MARKOV CHAIN

Stephen Berg, hyebin song, 2023, Annals of Statistics on p. 2440-2470

Non-covalent Lasso Entanglements in Folded Proteins: Prevalence, Functional Implications, and Evolutionary Significance

Viraj Rana, Ian Sitarik, Justin Petucci, Yang Jiang, Hyebin Song, Edward P. O'Brien, 2024, Journal of Molecular Biology

Prediction in the Presence of Response-Dependent Missing Labels

Hyebin Song, Garvesh Raskutti, Rebecca Willett, 2021, on p. 451-455

Convergence guarantee for the sparse monotone single index model<sup>∗</sup>

Ran Dai, Hyebin Song, Rina Foygel Barber, Garvesh Raskutti, 2022, Electronic Journal of Statistics on p. 4449-4496

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

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

Nurd: Negative-unlabeled learning for online datacenter straggler prediction

Yi Ding, Avinash Rao, Hyebin Song, Rebecca Willett, Henry Hoffmann, 2022, Proceedings of Machine Learning and Systems on p. 190--203