Publications

December 2020 Advances in Neural Information Processing Systems 33

A Shooting Formulation of Deep Learning

Selected for oral presentation

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October 2020 arXiv preprint arXiv:2010.11560

Deep Learning is Singular, and That's Good

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August 2020 arXiv preprint arXiv:2008.10797

The Fairness-Accuracy Pareto Front

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January 2020 arXiv preprint arXiv:2008.09289

Automating the assessment of biofouling in images using expert agreement as a gold standard

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October 2018 Biometrika

The change-plane Cox model

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February 2018 Electronic Journal of Statistics

Empirical evolution equations

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January 2018 2018 IEEE EMBS International Conference on Biomedical & Health Informatics (BHI)

Reinforcement-learning optimal control for type-1 diabetes

January 2018 2018 IEEE 28th International Workshop on Machine Learning for Signal Processing (MLSP)

Controlling Blood Glucose Levels In Patients With Type 1 Diabetes Using Fitted Q-Iterations And Functional Features

January 2018 Computational and mathematical methods in medicine

Control of blood glucose for type-1 diabetes by using reinforcement learning with feedforward algorithm

January 2018 Journal of nutrition education and behavior

A low-cost, grab-and-go breakfast intervention for rural high school students: Changes in school breakfast program participation among at-risk students in Minnesota

January 2017 WILEY

Statistical Scale Space Methods

January 2017 Journal of School Health

School breakfast program participation and rural adolescents' purchasing behaviors in food stores and restaurants

January 2017 Springer US

Mobile monitoring of traumatic brain injury in older adults: challenges and opportunities

May 2016 Journal of Computational and Graphical Statistics

Direction-projection-permutation for high-dimensional hypothesis tests

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September 2013 Journal of the American Statistical Association

Latent supervised learning

Selected as Featured Article

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January 2012 Histopathology

Image and statistical analysis of melanocytic histology

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January 2011

Discussion of “Adaptive Confidence Intervals for the Test Error in Classification”, by EB Laber and SA Murphy

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