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ORCIDMichael Lingzhi Li
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- affiliation: Massachusetts Institute of Technology, Cambridge, MA, USA
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2020 – today
- 2024
[j7]Dimitris Bertsimas
, Kimberly Villalobos Carballo, Léonard Boussioux, Michael Lingzhi Li, Alex Paskov, Ivan S. Paskov:
Holistic deep learning. Mach. Learn. 113(1): 159-183 (2024)- [i14]Zeyang Jia, Kosuke Imai, Michael Lingzhi Li:
The Cram Method for Efficient Simultaneous Learning and Evaluation. CoRR abs/2403.07031 (2024) - [i13]Michael Lingzhi Li, Kosuke Imai:
Neyman Meets Causal Machine Learning: Experimental Evaluation of Individualized Treatment Rules. CoRR abs/2404.17019 (2024) - [i12]Alexandre Jacquillat, Michael Lingzhi Li:
Learning to Cover: Online Learning and Optimization with Irreversible Decisions. CoRR abs/2406.14777 (2024) - [i11]Michael Lingzhi Li, Shixiang Zhu:
Balancing Optimality and Diversity: Human-Centered Decision Making through Generative Curation. CoRR abs/2409.11535 (2024) - 2023
- [j6]Dimitris Bertsimas, Michael Lingzhi Li:
Interpretable Matrix Completion: A Discrete Optimization Approach. INFORMS J. Comput. 35(5): 952-965 (2023) - [j5]Dimitris Bertsimas, Michael Lingzhi Li, Xinggang Liu, Jennings Xu, Najat Khan:
Data-Driven COVID-19 Vaccine Development for Janssen. INFORMS J. Appl. Anal. 53(1): 70-84 (2023) - [j4]Michael Lingzhi Li, Hamza Tazi Bouardi, Omar Skali Lami, Thomas A. Trikalinos, Nikolaos Trichakis, Dimitris Bertsimas:
Forecasting COVID-19 and Analyzing the Effect of Government Interventions. Oper. Res. 71(1): 184-201 (2023) - [c2]Junling Liu, Peilin Zhou, Yining Hua, Dading Chong, Zhongyu Tian, Andrew Liu, Helin Wang, Chenyu You, Zhenhua Guo, Lei Zhu, Michael Lingzhi Li:
Benchmarking Large Language Models on CMExam - A comprehensive Chinese Medical Exam Dataset. NeurIPS 2023 - [i10]Junling Liu, Peilin Zhou, Yining Hua, Dading Chong, Zhongyu Tian, Andrew Liu, Helin Wang, Chenyu You, Zhenhua Guo, Lei Zhu, Michael Lingzhi Li:
Benchmarking Large Language Models on CMExam - A Comprehensive Chinese Medical Exam Dataset. CoRR abs/2306.03030 (2023) - 2022
- [j3]Dimitris Bertsimas, Michael Lingzhi Li:
Stochastic Cutting Planes for Data-Driven Optimization. INFORMS J. Comput. 34(5): 2400-2409 (2022) - [j2]Luis R. Soenksen, Yu Ma, Cynthia Zeng, Léonard Boussioux, Kimberly Villalobos Carballo, Liangyuan Na, Holly M. Wiberg, Michael Lingzhi Li, Ignacio Fuentes, Dimitris Bertsimas:
Integrated multimodal artificial intelligence framework for healthcare applications. npj Digit. Medicine 5 (2022) - [i9]Luis R. Soenksen, Yu Ma, Cynthia Zeng, Léonard D. J. Boussioux, Kimberly Villalobos Carballo, Liangyuan Na, Holly M. Wiberg, Michael Lingzhi Li, Ignacio Fuentes, Dimitris Bertsimas:
Integrated multimodal artificial intelligence framework for healthcare applications. CoRR abs/2202.12998 (2022) - [i8]Dimitris Bertsimas, Kosuke Imai, Michael Lingzhi Li:
Distributionally Robust Causal Inference with Observational Data. CoRR abs/2210.08326 (2022) - 2021
- [i7]Dimitris Bertsimas, Vassilis Digalakis Jr., Michael Lingzhi Li, Omar Skali Lami:
Slowly Varying Regression under Sparsity. CoRR abs/2102.10773 (2021) - [i6]Dimitris Bertsimas, Léonard Boussioux, Kimberly Villalobos Carballo, Michael Lingzhi Li, Alex Paskov, Ivan S. Paskov:
Holistic Deep Learning. CoRR abs/2110.15829 (2021) - 2020
- [j1]Dimitris Bertsimas, Michael Lingzhi Li:
Scalable holistic linear regression. Oper. Res. Lett. 48(3): 203-208 (2020) - [c1]Michael Lingzhi Li, Elliott Wolf, Daniel Wintz:
Duration-of-Stay Storage Assignment under Uncertainty. ICLR 2020
2010 – 2019
- 2019
- [i5]Dimitris Bertsimas, Michael Lingzhi Li:
Accounting for Significance and Multicollinearity in Building Linear Regression Models. CoRR abs/1902.03272 (2019) - [i4]Michael Lingzhi Li, Elliott Wolf, Daniel Wintz:
Application of Duration-of-Stay Storage Assignment with Deep Neural Networks under Uncertainty. CoRR abs/1903.05063 (2019) - [i3]Dimitris Bertsimas, Michael Lingzhi Li:
Fast Exact Matrix Completion: A Unifying Optimization Framework. CoRR abs/1910.09092 (2019) - [i2]Michael Lingzhi Li, Meng Dong, Jiawei Zhou, Alexander M. Rush:
A Hierarchy of Graph Neural Networks Based on Learnable Local Features. CoRR abs/1911.05256 (2019) - 2018
- [i1]Dimitris Bertsimas, Michael Lingzhi Li:
Interpretable Matrix Completion: A Discrete Optimization Approach. CoRR abs/1812.06647 (2018)
Coauthor Index
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last updated on 2024-10-15 20:44 CEST by the dblp team
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