16 citations · 18 across the 7 of their papers we have counts for
7 papers
Improving Survival Models in Healthcare by Balancing Imbalanced Cohorts: A Novel Approach
Catherine Ning, Dimitris Bertsimas, Johan Gagnière +11
We explore whether survival model performance in underrepresented high- and low-risk subgroups - regions of the prognostic spectrum where clinical decisions are most consequential…
Should We Relax Stability in Matching Markets?
Dimitris Bertsimas, Carol Gao
Centralized assignment markets have historically relied on Deferred-Acceptance (DA) algorithms, which do not incorporate multiple objectives into the assignment. In this work, we p…
Robust and Adaptive Optimization under a Large Language Model Lens
Dimitris Bertsimas, Georgios Margaritis
In this paper, we explore the application of ChatGPT in the domain of Robust and Adaptive Robust Optimization. We demonstrate that with appropriate prompting, ChatGPT can be used t…
The R.O.A.D. to clinical trial emulation
Dimitris Bertsimas, Angelos G. Koulouras, Hiroshi Nagata +4
Observational studies provide the only evidence on the effectiveness of interventions when randomized controlled trials (RCTs) are impractical due to cost, ethical concerns, or tim…
Global Optimization: A Machine Learning Approach
Dimitris Bertsimas, Georgios Margaritis
Many approaches for addressing Global Optimization problems typically rely on relaxations of nonlinear constraints over specific mathematical primitives. This is restricting in app…
The R.O.A.D. to precision medicine
Dimitris Bertsimas, Angelos G. Koulouras, Georgios Antonios Margonis
We propose a prognostic stratum matching framework that addresses the deficiencies of Randomized trial data subgroup analysis and transforms ObservAtional Data to be used as if the…
Robust Regression over Averaged Uncertainty
Dimitris Bertsimas, Yu Ma
We propose a new formulation of robust regression by integrating all realizations of the uncertainty set and taking an averaged approach to obtain the optimal solution for the ordi…