Finale Doshi-velez
Affiliations: | Computer Science | Harvard University, Cambridge, MA, United States |
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"Finale Doshi-velez"
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| Nofshin E, Swaroop S, Pan W, et al. (2024) Reinforcement Learning Interventions on Boundedly Rational Human Agents in Frictionful Tasks. Proceedings of the ... International Joint Conference On Autonomous Agents and Multiagent Systems : Aamas. International Joint Conference On Autonomous Agents and Multiagent Systems. 2024: 1482-1491 |
| Shin E, Klasnja P, Murphy SA, et al. (2024) Online model selection by learning how compositional kernels evolve. Transactions On Machine Learning Research. 2023 |
| Rathnam S, Parbhoo S, Pan W, et al. (2023) The Unintended Consequences of Discount Regularization: Improving Regularization in Certainty Equivalence Reinforcement Learning. Proceedings of Machine Learning Research. 202: 28746-28767 |
| Trella AL, Zhang KW, Nahum-Shani I, et al. (2023) Reward Design For An Online Reinforcement Learning Algorithm Supporting Oral Self-Care. Proceedings of the ... Innovative Applications of Artificial Intelligence Conference. Innovative Applications of Artificial Intelligence Conference. 37: 15724-15730 |
| Trella AL, Zhang KW, Nahum-Shani I, et al. (2022) Designing Reinforcement Learning Algorithms for Digital Interventions: Pre-Implementation Guidelines. Algorithms. 15 |
| Johnson N, Parbhoo S, Ross AS, et al. (2022) Learning Predictive and Interpretable Timeseries Summaries from ICU Data. Amia ... Annual Symposium Proceedings. Amia Symposium. 2021: 581-590 |
| Yao J, Brunskill E, Pan W, et al. (2021) Power Constrained Bandits. Proceedings of Machine Learning Research. 149: 209-259 |
| Jacobs M, Pradier MF, McCoy TH, et al. (2021) How machine-learning recommendations influence clinician treatment selections: the example of the antidepressant selection. Translational Psychiatry. 11: 108 |
| Lu M, Shahn Z, Sow D, et al. (2020) Is Deep Reinforcement Learning Ready for Practical Applications in Healthcare? A Sensitivity Analysis of Duel-DDQN for Hemodynamic Management in Sepsis Patients. Amia ... Annual Symposium Proceedings. Amia Symposium. 2020: 773-782 |
| Futoma J, Simons M, Panch T, et al. (2020) The myth of generalisability in clinical research and machine learning in health care. The Lancet. Digital Health. 2: e489-e492 |