| Understanding how dimension reduction tools work: an empirical approach to deciphering t-SNE, UMAP, TriMAP, and PaCMAP for data visualization Y Wang, H Huang, C Rudin, Y Shaposhnik Journal of Machine Learning Research 22 (201), 1-73, 2021 | 680 | 2021 |
| A holistic approach to interpretability in financial lending: Models, visualizations, and summary-explanations C Chen, K Lin, C Rudin, Y Shaposhnik, S Wang, T Wang Decision Support Systems 152, 113647, 2022 | 203* | 2022 |
| Globally-consistent rule-based summary-explanations for machine learning models: application to credit-risk evaluation C Rudin, Y Shaposhnik Journal of Machine Learning Research 24 (16), 1-44, 2023 | 66 | 2023 |
| Scheduling with testing R Levi, T Magnanti, Y Shaposhnik Management Science 65 (2), 776-793, 2019 | 47 | 2019 |
| Mining optimal policies: A pattern recognition approach to model analysis F Bravo, Y Shaposhnik INFORMS Journal on Optimization 2 (3), 145-166, 2020 | 37 | 2020 |
| The pandora's box problem with sequential inspections A Aouad, J Ji, Y Shaposhnik arXiv preprint arXiv:2507.07508, 2025 | 23 | 2025 |
| Interpretable prediction rules for congestion risk in intensive care units F Bravo, C Rudin, Y Shaposhnik, Y Yuan Stochastic Systems 14 (2), 111-130, 2024 | 15* | 2024 |
| A polynomial-time approximation scheme for sequential batch testing of series systems D Segev, Y Shaposhnik Operations Research 70 (2), 1153-1165, 2022 | 14 | 2022 |
| Optimal ordering for a probabilistic one-time discount Y Shaposhnik, YT Herer, H Naseraldin European Journal of Operational Research 244 (3), 803-814, 2015 | 13 | 2015 |
| Exploration vs. Exploitation: reducing uncertainty in operational problems Y Shaposhnik Massachusetts Institute of Technology, 2016 | 9 | 2016 |
| Stochastic selection problems with testing C Attias, R Krauthgamer, R Levi, Y Shaposhnik Available at SSRN 3076956, 2017 | 7 | 2017 |
| Scheduling with testing of heterogeneous jobs R Levi, T Magnanti, Y Shaposhnik Management Science 70 (5), 2934-2953, 2024 | 6* | 2024 |
| Waiting Time Prediction with Invisible Customers Y Kerner, R Roet-Green, A Senderovich, Y Shaposhnik, Y Yuan Manufacturing & Service Operations Management, 2025 | 4 | 2025 |
| Visualizing the Implicit Model Selection Tradeoff Z He, Y Shaposhnik Journal of Artificial Intelligence Research 76, 829-881, 2023 | 3 | 2023 |
| A dual-index rule for managing temporary congestion Y Shaposhnik European Journal of Operational Research 323 (1), 34-44, 2025 | 1 | 2025 |
| Algorithm Adoption and Explanations: An Experimental Study on Self and Other Perspectives F Bravo, ZD He, Y Shaposhnik, L Valdés Available at SSRN 5017247, 2024 | 1 | 2024 |
| Explaining Model Behavior Across Space and Time: Differential and Intertemporal Explanations ZD He, Y Shaposhnik Available at SSRN 5277675, 2025 | | 2025 |
Cynthia RudinProfessor of Computer Science, ECE, Statistics, and Biostatistics & Bioinformatics, Duke UniversityVerified email at cs.duke.edu
