Publications

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^† indicates equal contributions
^* indicates corresponding author(s)

Preprints

Hyebin Song^†, Stephen Berg^†*, Multivariate moment least-squares estimators for reversible Markov chains, Submitted, ArXiv preprint, 2023+. [Paper]

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Publications

Viraj Rana^†, Ian Sitarik^†, Justin Petucci, Yang Jiang, Hyebin Song^*, Edward O’Brien^*, Non-covalent Lasso Entanglements in Folded Proteins: Prevalence, Functional Implications, and Evolutionary Significance, Journal of Molecular Biology, 2024. [Paper]

Stephen Berg^†, Hyebin Song^†*. Efficient shape-constrained inference for the autocovariance sequence from a reversible Markov chain, In press, Annals of Statistics, 2023. [Paper]

Sameer D’Costa^†, Emily C. Hinds^†, Chase R. Freschlin, Hyebin Song^*, Philip A. Romero^* Inferring protein fitness landscapes from laboratory evolution experiments, PLOS Computational Biology, 2023. [Paper]

Ran Dai, Hyebin Song, Rina Foygel Barber^*, Garvesh Raskutti. Convergence guarantee for the sparse monotone single index model, Electronic Journal of Statistics, 2022. [Paper]

Yi Ding^*, Avinash Rao, Hyebin Song, Rebecca Willett, Henry Hank Hoffmann. NURD: Negative-Unlabeled Learning for Online Datacenter Straggler Prediction, Proceedings of Machine Learning and Systems, 2022. [Paper]

Hyebin Song^*, Garvesh Raskutti, Rebecca Willett. Prediction in the presence of response-dependent missing labels, IEEE Statistical Signal Processing Workshop 2021, 2021. [Paper]

Hyebin Song, Bennett J. Bremer, Emily C. Hinds, Garvesh Raskutti, Philip A. Romero^*. Inferring protein sequence-function relationships with large-scale positive-unlabeled learning, Cell Systems, 2020. [Paper]

Hyebin Song^*, Ran Dai, Garvesh Raskutti, Rina Foygel Barber. Convex and Non-convex Approaches for Statistical Inference with Class-Conditional Noisy Labels. Journal of Machine Learning Research, 2020. [Paper]

Yuan Li^†, Benjamin Mark^†*, Garvesh Raskutti, Rebecca Willett, Hyebin Song, David Neiman. Graph-based regularization for regression problems with alignment and highly-correlated designs. SIAM Journal on Mathematics of Data Science (SIMODS), 2020. [Paper]

Ran Dai, Hyebin Song, Rina Foygel Barber^*, Garvesh Raskutti. The bias of isotonic regression. Electronic Journal of Statistics, 2020. [Paper]

Hyebin Song^*, Garvesh Raskutti. PUlasso: High-Dimensional Variable Selection With Presence-Only Data. Journal of the American Statistical Association, 2019. [Paper] [Code]