Hyebin Song
Assistant Professor of Statistics
-
414 Thomas`
University Park, PA - hps5320@psu.edu
- 814-865-3631
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
Multivariate moment least-squares estimators for reversible Markov chains
Hyebin Song, S Berg, Journal of Computational and Graphical Statistics
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 on p. 168459
Multivariate Moment Least-Squares Variance Estimators for Reversible Markov Chains
hyebin song, Stephen Berg, 2024, Journal of Computational and Graphical Statistics
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
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
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
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
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
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
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
Multivariate Moment Least-Squares Variance Estimators for Reversible Markov Chains
hyebin song, Stephen Berg, 2024, Journal of Computational and Graphical Statistics
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 on p. 168459