Shengpu Tang

According to our database, Shengpu Tang authored at least 13 papers between 2019 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

CANDOR: Counterfactual ANnotated DOubly Robust Off-Policy Evaluation.

Aishwarya Mandyam, Shengpu Tang, Jiayu Yao, Jenna Wiens, Barbara E. Engelhardt

CoRR, 2024

2023

Machine Learning for Health symposium 2023 - Findings track.

Stefan Hegselmann, Antonio Parziale, Divya Shanmugam, Shengpu Tang, Mercy Nyamewaa Asiedu, Serina Chang, Thomas Hartvigsen, Harvineet Singh

CoRR, 2023

Leveraging Factored Action Spaces for Off-Policy Evaluation.

Aaman Rebello, Shengpu Tang, Jenna Wiens, Sonali Parbhoo

CoRR, 2023

Counterfactual-Augmented Importance Sampling for Semi-Offline Policy Evaluation.

Shengpu Tang, Jenna Wiens

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Machine Learning for Health (ML4H) 2023.

Stefan Hegselmann, Antonio Parziale, Divya Shanmugam, Shengpu Tang, Kristen Severson, Mercy Nyamewaa Asiedu, Serina Chang, Bonaventure F. P. Dossou, Qian Huang, Fahad Kamran, Haoran Zhang, Sujay Nagaraj, Luis Oala, Shan Xu, Chinasa T. Okolo, Helen Zhou, Jessica Dafflon, Caleb Ellington, Sarah Jabbour, Hyewon Jeong, Harry Reyes Nieva, Yuzhe Yang, Ghada Zamzmi, Vishwali Mhasawade, Van Truong, Payal Chandak, Matthew Lee, Peniel Argaw, Kyle Heuton, Harvineet Singh, Thomas Hartvigsen

Proceedings of the Machine Learning for Health, 2023

2022

Machine Learning for Health symposium 2022 - Extended Abstract track.

Antonio Parziale, Monica Agrawal, Shalmali Joshi, Irene Y. Chen, Shengpu Tang, Luis Oala, Adarsh Subbaswamy

CoRR, 2022

Towards Data-Driven Offline Simulations for Online Reinforcement Learning.

Shengpu Tang, Felipe Vieira Frujeri, Dipendra Misra, Alex Lamb, John Langford, Paul Mineiro, Sebastian Kochman

CoRR, 2022

Leveraging Factored Action Spaces for Efficient Offline Reinforcement Learning in Healthcare.

Shengpu Tang, Maggie Makar, Michael W. Sjoding, Finale Doshi-Velez, Jenna Wiens

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Machine Learning for Health (ML4H) 2022.

Antonio Parziale, Monica Agrawal, Shengpu Tang, Kristen Severson, Luis Oala, Adarsh Subbaswamy, Sayantan Kumar, Elora D. M. Schörverth, Stefan Hegselmann, Helen Zhou, Ghada Zamzmi, Purity Mugambi, Elena Sizikova, Girmaw Abebe Tadesse, Yuyin Zhou, Taylor W. Killian, Haoran Zhang, Fahad Kamran, Andrea Hobby, Mars Huang, Ahmed M. Alaa, Harvineet Singh, Irene Y. Chen, Shalmali Joshi

Proceedings of the Machine Learning for Health, 2022

2021

Model Selection for Offline Reinforcement Learning: Practical Considerations for Healthcare Settings.

Shengpu Tang, Jenna Wiens

Proceedings of the Machine Learning for Healthcare Conference, 2021

2020

Democratizing EHR analyses with FIDDLE: a flexible data-driven preprocessing pipeline for structured clinical data.

Shengpu Tang, Parmida Davarmanesh, Yanmeng Song, Danai Koutra, Michael W. Sjoding, Jenna Wiens

J. Am. Medical Informatics Assoc., 2020

Clinician-in-the-Loop Decision Making: Reinforcement Learning with Near-Optimal Set-Valued Policies.

Shengpu Tang, Aditya Modi, Michael W. Sjoding, Jenna Wiens

Proceedings of the 37th International Conference on Machine Learning, 2020

2019

Relaxed Parameter Sharing: Effectively Modeling Time-Varying Relationships in Clinical Time-Series.

Jeeheh Oh, Jiaxuan Wang, Shengpu Tang, Michael W. Sjoding, Jenna Wiens

Proceedings of the Machine Learning for Healthcare Conference, 2019