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Papers

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A Machine Learning Approach to Two-Stage Adaptive Robust Optimization

with Cheol Woo Kim, submitted to European Journal of Operation Research, 2023

A Prescriptive Machine Learning Approach to Mixed-Integer Convex Optimization

with Cheol Woo Kim, INFORMS Journal on Computing, 2023

A Simulated Annealing Approach to Designing Optimal Policy Trees

with Suleeporn Sujichantararat, submitted to Machine Learning, 2023

A Stochastic Benders Decomposition Scheme for Large-Scale Data-Driven Network Design

with R. Cory-Wright, J. Pauphilet, P. Petridis, submitted to INFORMS Journal of Computing, 2023

A data-driven approach to multistage stochastic linear optimization

with Shimrit Shtern, Bradley Sturt, Management Science 69(1):51-74, 2023

A new perspective on low-rank optimization, 2023

with Ryan Cory-Wright, Jean Pauphilet, Mathematical Programming, 2023

A novel algorithm for a broad class of nonconvex optimization problems

with D. de Moor, T. Koukouvinos, D. den Hertog, J. Zhen, submitted to Operations Research, 2023

Accelerating Vaccine Innovation for Emerging Infectious Diseases via Parallel Discovery

with Joseph Barberio, Jacob Becraft, Zied Ben Chaouch, Tasuku Kitada, Michael L Li, Andrew W Lo, Kevin Shi, Qingyang Xu, 2023

Adaptive Linear Algebra

with Thodoris Koukouvinos, 2023

Adaptive Pricing in Unit Commitment Under Load and Capacity Uncertainty

with Angelos Georgios Koulouras, IEEE Transactions on Power Systems, 2023

Automated Segmentation of Sacral Chordoma and Surrounding Muscles Using Deep Learning Ensemble

with Leonard Boussioux, Yu Ma, Nancy Knight Thomas, Nadya Shusharina, Jennifer Pursley, Yen-Lin Chen, Thomas F. DeLaney, Jack Qian, Thomas Bortfeld, International Journal of Radiation Oncology - Biology - Physics, 2023

Compressed Sensing: A Discrete Optimization Approach

with Nicholas Johnson, 2023

Cone product reformulation for global optimization

with Danique de Moor, Dick den Hertog, Thodoris Koukouvinos, Jianzhe Zhen, submitted to INFORMS Journal of Computing, 2023

Data-Driven COVID-19 Vaccine Development for Janssen

with Michael Lingzhi Li, Xinggang Liu, Jennings Xu, Najat Khan, INFORMS Journal on Applied Analytics, 2023

Development of a Machine Learning Based Prescriptive Tool to Address Racial Disparities in Access to Care After Penetrating Trauma

with Anthony Gebran, Sumiran S. Thakur, Lydia R. Maurer, Hari Bandi, Robert Sinyard, Ander Dorken-Gallastegi, Mary Bokenkamp, Mohamad El Moheb, Leon Naar, Annita Vapsi, Dania Daye, George C Velmahos, Haytham M.A. Kaafarani, JAMA Surgery, 2023

Distributionally Robust Causal Inference with Observational Data

with Kosuke Imai, Michael Lingzhi Li, submitted to Journal of Machine Learning Research, 2023

Dynamic Optimization with Side Information

with C. McCord and B. Sturt, European Journal of Operations Research, 2023

Ensemble Modeling for Time Series Forecasting: an Adaptive Robust Optimization Approach

with L. Boussioux, submitted to Journal of Machine Learning Research, 2023

Ensembling Wind Forecasting Models to Construct Data-Driven Uncertainty Sets in Robust Optimization

with Panagiotis Andrianesis, Thodoris Koukouvinos, Angelos Georgios Koulouras, submitted to IEEE Power systems, 2023

Explainable vs. interpretable artificial intelligence frameworks in oncology

with Georgios Antonios Margonis, Transl Cancer Res 2023;12(2):217, 2023

Finding neurons in a Haystack - Case studies with sparse probing

with Wes Gurnee, Neel Nanda, Matthew Pauly, Katherine Harvey, Dmitrii Troitskii, 2023

Forecasting COVID-19 and analyzing the effect of government interventions

with Michael Lingzhi Li, Hamza Tazi Bouardi, Omar Skali Lami, Thomas A Trikalinos, Nikolaos Trichakis, Operations Research 71(1):184-201, 2023

Global Flood Prediction: a Multimodal Machine Learning Approach

with Cynthia Zeng, arXiv preprint arXiv:2301.12548, 2023

High-performance pediatric surgical risk calculator: A novel algorithm based on machine learning and pediatric NSQIP data

with Michael Li, Nova Zhang, Carlos Estrada, Hsin-Hsiao Scott Wang, The American Journal of Surgery, 2023

Holistic Deep Learning

with L. Boussioux, K. Villalobos Carballo, M. Li, A. Paskov and I. Paskov, submitted to Machine Learning, 2023