| 2025 | ICML | Decision-aware Training of Spatiotemporal Forecasting Models to Select a Top-K Subset of Sites for Intervention. | Kyle Heuton, F. Samuel Muench, Shikhar Shrestha, Thomas J. Stopka, Michael C. Hughes |
| 2024 | CVPR | Systematic comparison of semi-supervised and self-supervised learning for medical image classification. | Zhe Huang, Ruijie Jiang, Shuchin Aeron, Michael C. Hughes |
| 2024 | ICML | InterLUDE: Interactions between Labeled and Unlabeled Data to Enhance Semi-Supervised Learning. | Zhe Huang, Xiaowei Yu, Dajiang Zhu, Michael C. Hughes |
| 2023 | AISTATS | Fix-A-Step: Semi-supervised Learning From Uncurated Unlabeled Data. | Zhe Huang, Mary-Joy Sidhom, Benjamin Wessler, Michael C. Hughes |
| 2022 | AISTATS | Optimizing Early Warning Classifiers to Control False Alarms via a Minimum Precision Constraint. | Preetish Rath, Michael C. Hughes |
| 2022 | ICML | Easy Variational Inference for Categorical Models via an Independent Binary Approximation. | Michael T. Wojnowicz, Shuchin Aeron, Eric L. Miller, Michael C. Hughes |
| 2021 | ICML | Stochastic Iterative Graph Matching. | Linfeng Liu, Michael C. Hughes, Soha Hassoun, Liping Liu |
| 2021 | UIST | Taming fNIRS-based BCI Input for Better Calibration and Broader Use. | Liang Wang, Zhe Huang, Ziyu Zhou, Devon McKeon, Giles Blaney, Michael C. Hughes, Robert J. K. Jacob |
| 2020 | AAAI | Regional Tree Regularization for Interpretability in Deep Neural Networks. | Mike Wu, Sonali Parbhoo, Michael C. Hughes, Ryan Kindle, Leo A. Celi, Maurizio Zazzi, Volker Roth, Finale Doshi-Velez |
| 2020 | AISTATS | POPCORN: Partially Observed Prediction Constrained Reinforcement Learning. | Joseph Futoma, Michael C. Hughes, Finale Doshi-Velez |
| 2020 | ICASSP | Optimal Transport Based Change Point Detection and Time Series Segment Clustering. | Kevin C. Cheng, Shuchin Aeron, Michael C. Hughes, Erika Hussey, Eric L. Miller |
| 2018 | AAAI | Beyond Sparsity: Tree Regularization of Deep Models for Interpretability. | Mike Wu, Michael C. Hughes, Sonali Parbhoo, Maurizio Zazzi, Volker Roth, Finale Doshi-Velez |
| 2018 | AISTATS | Semi-Supervised Prediction-Constrained Topic Models. | Michael C. Hughes, Gabriel Hope, Leah Weiner, Thomas H. McCoy Jr., Roy H. Perlis, Erik B. Sudderth, Finale Doshi-Velez |
| 2017 | ICML | From Patches to Images: A Nonparametric Generative Model. | Geng Ji, Michael C. Hughes, Erik B. Sudderth |
| 2017 | IJCAI | Right for the Right Reasons: Training Differentiable Models by Constraining their Explanations. | Andrew Slavin Ross, Michael C. Hughes, Finale Doshi-Velez |
| 2015 | AISTATS | Reliable and Scalable Variational Inference for the Hierarchical Dirichlet Process. | Michael C. Hughes, Dae Il Kim, Erik B. Sudderth |
| 2012 | CVPR | Nonparametric discovery of activity patterns from video collections. | Michael C. Hughes, Erik B. Sudderth |
| 2012 | ICML | The Nonparametric Metadata Dependent Relational Model. | Dae Il Kim, Michael C. Hughes, Erik B. Sudderth |