Stop the war!Остановите войну!
for scientists:
default search action
Google
Google Scholar
Semantic Scholar
Internet Archive Scholar
CiteSeerX
ORCIDDimitris Bertsimas
Dimitris J. Bertsimas
Person information
- affiliation: Massachusetts Institute of Technology, Cambridge, MA, USA
Refine list
refinements active!
zoomed in on ?? of ?? records
view refined list in
export refined list as
showing all ?? records
2020 – today
- 2024
[j226]Dimitris Bertsimas, Thodoris Koukouvinos:
Robust linear algebra. Eur. J. Oper. Res. 314(3): 1174-1184 (2024)- [j225]Dimitris Bertsimas, Cheol Woo Kim:
A machine learning approach to two-stage adaptive robust optimization. Eur. J. Oper. Res. 319(1): 16-30 (2024) - [j224]Dimitris Bertsimas
, Jean Pauphilet:
Hospital-Wide Inpatient Flow Optimization. Manag. Sci. 70(7): 4893-4911 (2024) - [j223]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) - [j222]Dimitris Bertsimas, Nicholas A. G. Johnson:
Compressed sensing: a discrete optimization approach. Mach. Learn. 113(9): 6725-6764 (2024) - [j221]Dimitris Bertsimas, Stefan C. M. ten Eikelder, Dick den Hertog, Nikolaos Trichakis:
Pareto Adaptive Robust Optimality via a Fourier-Motzkin Elimination lens. Math. Program. 205(1): 485-538 (2024) - [j220]Dimitris Bertsimas, Arthur Delarue, Jean Pauphilet:
Simple Imputation Rules for Prediction with Missing Data: Theoretical Guarantees vs. Empirical Performance. Trans. Mach. Learn. Res. 2024 (2024) - [j219]Wes Gurnee, Theo Horsley, Zifan Carl Guo, Tara Rezaei Kheirkhah, Qinyi Sun, Will Hathaway, Neel Nanda, Dimitris Bertsimas:
Universal Neurons in GPT2 Language Models. Trans. Mach. Learn. Res. 2024 (2024) - [i61]Wes Gurnee, Theo Horsley, Zifan Carl Guo, Tara Rezaei Kheirkhah, Qinyi Sun, Will Hathaway, Neel Nanda, Dimitris Bertsimas:
Universal Neurons in GPT2 Language Models. CoRR abs/2401.12181 (2024) - [i60]Dimitris Bertsimas, Arthur Delarue, Jean Pauphilet:
Adaptive Optimization for Prediction with Missing Data. CoRR abs/2402.01543 (2024) - [i59]Vassilis Digalakis Jr., Yu Ma, Phevos Paschalidis, Dimitris Bertsimas:
Towards Stable Machine Learning Model Retraining via Slowly Varying Sequences. CoRR abs/2403.19871 (2024) - [i58]Dimitris Bertsimas, Yu Ma:
M3H: Multimodal Multitask Machine Learning for Healthcare. CoRR abs/2404.18975 (2024) - [i57]Dimitris Bertsimas, Cynthia Zeng:
Catastrophe Insurance: An Adaptive Robust Optimization Approach. CoRR abs/2405.07068 (2024) - [i56]Dimitris Bertsimas, Matthew Peroni:
Policy Trees for Prediction: Interpretable and Adaptive Model Selection for Machine Learning. CoRR abs/2405.20486 (2024) - [i55]Dimitris Bertsimas, Nicholas A. G. Johnson:
Predictive Low Rank Matrix Learning under Partial Observations: Mixed-Projection ADMM. CoRR abs/2407.13731 (2024) - 2023
- [j218]Dimitris Bertsimas, Christopher McCord, Bradley Sturt:
Dynamic optimization with side information. Eur. J. Oper. Res. 304(2): 634-651 (2023) - [j217]Dimitris Bertsimas, Michael Lingzhi Li:
Interpretable Matrix Completion: A Discrete Optimization Approach. INFORMS J. Comput. 35(5): 952-965 (2023) - [j216]Dimitris Bertsimas, Cheol Woo Kim:
A Prescriptive Machine Learning Approach to Mixed-Integer Convex Optimization. INFORMS J. Comput. 35(6): 1225-1241 (2023) - [j215]Dimitris Bertsimas, Nathan Kallus:
The Power and Limits of Predictive Approaches to Observational Data-Driven Optimization: The Case of Pricing. INFORMS J. Optim. 5(1): 110-129 (2023) - [j214]Dimitris Bertsimas, Omar Skali Lami:
Holistic Prescriptive Analytics for Continuous and Constrained Optimization Problems. INFORMS J. Optim. 5(2): 155-171 (2023) - [j213]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) - [j212]Theodore Papalexopoulos, James B. Alcorn, Dimitris Bertsimas, Rebecca E. Goff, Darren E. Stewart, Nikolaos Trichakis:
Applying Analytics to Design Lung Transplant Allocation Policy. INFORMS J. Appl. Anal. 53(5): 350-358 (2023) - [j211]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) - [j210]Dimitris Bertsimas, Arthur Delarue:
Policy Analytics in Public School Operations. Oper. Res. 71(1): 289-313 (2023) - [j209]Dimitris Bertsimas, Nishanth Mundru:
Optimization-Based Scenario Reduction for Data-Driven Two-Stage Stochastic Optimization. Oper. Res. 71(4): 1343-1361 (2023) - [j208]Dimitris Bertsimas, Driss Lahlou Kitane:
Sparse PCA: a Geometric Approach. J. Mach. Learn. Res. 24: 32:1-32:33 (2023) - [j207]Dimitris Bertsimas, Shimrit Shtern, Bradley Sturt:
A Data-Driven Approach to Multistage Stochastic Linear Optimization. Manag. Sci. 69(1): 51-74 (2023) - [j206]Dimitris Bertsimas, Colin Pawlowski:
Tensor completion with noisy side information. Mach. Learn. 112(10): 3945-3976 (2023) - [j205]Dimitris Bertsimas, Dick den Hertog, Jean Pauphilet, Jianzhe Zhen:
Robust convex optimization: A new perspective that unifies and extends. Math. Program. 200(2): 877-918 (2023) - [j204]Dimitris Bertsimas, Ryan Cory-Wright, Jean Pauphilet:
A new perspective on low-rank optimization. Math. Program. 202(1): 47-92 (2023) - [j203]Dimitris Bertsimas, Ryan Cory-Wright, Jean Pauphilet:
Publisher Correction to: A new perspective on low-rank optimization. Math. Program. 202(1): 93-94 (2023) - [j202]Dimitris Bertsimas, Vassilis Digalakis:
Frequency Estimation in Data Streams: Learning the Optimal Hashing Scheme. IEEE Trans. Knowl. Data Eng. 35(2): 1541-1553 (2023) - [j201]Wes Gurnee, Neel Nanda, Matthew Pauly, Katherine Harvey, Dmitrii Troitskii, Dimitris Bertsimas:
Finding Neurons in a Haystack: Case Studies with Sparse Probing. Trans. Mach. Learn. Res. 2023 (2023) - [i54]Cynthia Zeng, Dimitris Bertsimas:
Global Flood Prediction: a Multimodal Machine Learning Approach. CoRR abs/2301.12548 (2023) - [i53]Dimitris Bertsimas, Kimberly Villalobos Carballo:
Multistage Stochastic Optimization via Kernels. CoRR abs/2303.06515 (2023) - [i52]Dimitris Bertsimas, Léonard Boussioux, Cynthia Zeng:
Reducing Air Pollution through Machine Learning. CoRR abs/2303.12285 (2023) - [i51]Dimitris Bertsimas, Léonard Boussioux:
Ensemble Modeling for Time Series Forecasting: an Adaptive Robust Optimization Approach. CoRR abs/2304.04308 (2023) - [i50]Wes Gurnee, Neel Nanda, Matthew Pauly, Katherine Harvey, Dmitrii Troitskii, Dimitris Bertsimas:
Finding Neurons in a Haystack: Case Studies with Sparse Probing. CoRR abs/2305.01610 (2023) - [i49]Dimitris Bertsimas, Ryan Cory-Wright, Sean Lo, Jean Pauphilet:
Optimal Low-Rank Matrix Completion: Semidefinite Relaxations and Eigenvector Disjunctions. CoRR abs/2305.12292 (2023) - [i48]Liangyuan Na, Kimberly Villalobos Carballo, Jean Pauphilet, Ali Haddad-Sisakht, Daniel Kombert, Melissa Boisjoli-Langlois, Andrew Castiglione, Maram Khalifa, Pooja Hebbal, Barry Stein, Dimitris Bertsimas:
Patient Outcome Predictions Improve Operations at a Large Hospital Network. CoRR abs/2305.15629 (2023) - [i47]Dimitris Bertsimas, Vassilis Digalakis Jr.:
Improving Stability in Decision Tree Models. CoRR abs/2305.17299 (2023) - [i46]Dimitris Bertsimas, Nicholas A. G. Johnson:
Compressed Sensing: A Discrete Optimization Approach. CoRR abs/2306.04647 (2023) - [i45]Dimitris Bertsimas, Cheol Woo Kim:
Optimal Control of Multiclass Fluid Queueing Networks: A Machine Learning Approach. CoRR abs/2307.12405 (2023) - [i44]Dimitris Bertsimas, Cheol Woo Kim:
A Machine Learning Approach to Two-Stage Adaptive Robust Optimization. CoRR abs/2307.12409 (2023) - [i43]Dimitris Bertsimas, Angelos G. Koulouras, Georgios Antonios Margonis:
The R.O.A.D. to precision medicine. CoRR abs/2311.01681 (2023) - [i42]Dimitris Bertsimas, Georgios Margaritis:
Global Optimization: A Machine Learning Approach. CoRR abs/2311.01742 (2023) - [i41]Dimitris Bertsimas, Yu Ma:
Robust Regression over Averaged Uncertainty. CoRR abs/2311.06960 (2023) - 2022
- [j200]Dimitris Bertsimas, Ryan Cory-Wright:
A Scalable Algorithm for Sparse Portfolio Selection. INFORMS J. Comput. 34(3): 1489-1511 (2022) - [j199]Dimitris Bertsimas, Bartolomeo Stellato:
Online Mixed-Integer Optimization in Milliseconds. INFORMS J. Comput. 34(4): 2229-2248 (2022) - [j198]Dimitris Bertsimas, Michael Lingzhi Li:
Stochastic Cutting Planes for Data-Driven Optimization. INFORMS J. Comput. 34(5): 2400-2409 (2022) - [j197]Adrian Becker, Kassem Benabderrazik, Dimitris Bertsimas, Nada Chtinna, Nada El Majdoub, El Miloudi Mahboubi, Driss Lahlou Kitane, Steve Kokkotos, Georgia Mourtzinou, Ilyas Rakhis:
Toward Global Food Security: Transforming OCP Through Analytics. INFORMS J. Appl. Anal. 52(1): 90-107 (2022) - [j196]Dimitris Bertsimas, Nihal Koduri:
Data-Driven Optimization: A Reproducing Kernel Hilbert Space Approach. Oper. Res. 70(1): 454-471 (2022) - [j195]Dimitris Bertsimas, Shimrit Shtern, Bradley Sturt:
Technical Note - Two-Stage Sample Robust Optimization. Oper. Res. 70(1): 624-640 (2022) - [j194]Dimitris Bertsimas, Ryan Cory-Wright, Jean Pauphilet:
Mixed-Projection Conic Optimization: A New Paradigm for Modeling Rank Constraints. Oper. Res. 70(6): 3321-3344 (2022) - [j193]Dimitris Bertsimas, Ryan Cory-Wright, Jean Pauphilet:
Solving Large-Scale Sparse PCA to Certifiable (Near) Optimality. J. Mach. Learn. Res. 23: 13:1-13:35 (2022) - [j192]Dimitris Bertsimas, Jack Dunn, Ivan S. Paskov:
Stable Classification. J. Mach. Learn. Res. 23: 296:1-296:53 (2022) - [j191]Dimitris Bertsimas, Vassilis Digalakis:
The backbone method for ultra-high dimensional sparse machine learning. Mach. Learn. 111(6): 2161-2212 (2022) - [j190]Dimitris Bertsimas, Jack Dunn, Emma Gibson, Agni Orfanoudaki:
Optimal survival trees. Mach. Learn. 111(8): 2951-3023 (2022) - [j189]Dimitris Bertsimas, Alex Paskov:
World-class interpretable poker. Mach. Learn. 111(8): 3063-3083 (2022) - [j188]Dimitris Bertsimas, Bart P. G. Van Parys:
Bootstrap robust prescriptive analytics. Math. Program. 195(1): 39-78 (2022) - [j187]Cynthia Barnhart, Dimitris Bertsimas, Arthur Delarue, Julia Yan:
Course Scheduling Under Sudden Scarcity: Applications to Pandemic Planning. Manuf. Serv. Oper. Manag. 24(2): 727-745 (2022) - [j186]Dimitris Bertsimas, Jean Pauphilet, Jennifer P. Stevens, Manu Tandon:
Predicting Inpatient Flow at a Major Hospital Using Interpretable Analytics. Manuf. Serv. Oper. Manag. 24(6): 2809-2824 (2022) - [j185]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) - [j184]Dimitris Bertsimas, Jack Dunn, Lea Kapelevich, Rebecca Zhang:
Sparse regression over clusters: SparClur. Optim. Lett. 16(2): 433-448 (2022) - [c23]Dimitris Bertsimas, Vassilis Digalakis:
Frequency Estimation in Data Streams: Learning the Optimal Hashing Scheme (Extended Abstract). ICDE 2022: 1565-1566 - [c22]Dimitris Bertsimas, Predrag V. Klasnja, Susan A. Murphy, Liangyuan Na:
Data-driven Interpretable Policy Construction for Personalized Mobile Health. ICDH 2022: 13-22 - [i40]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) - [i39]Dimitris Bertsimas, Wes Gurnee:
Learning Sparse Nonlinear Dynamics via Mixed-Integer Optimization. CoRR abs/2206.00176 (2022) - [i38]Dimitris Bertsimas, Kimberly Villalobos Carballo, Yu Ma, Liangyuan Na, Léonard Boussioux, Cynthia Zeng, Luis R. Soenksen, Ignacio Fuentes:
TabText: a Systematic Approach to Aggregate Knowledge Across Tabular Data Structures. CoRR abs/2206.10381 (2022) - [i37]Dimitris Bertsimas, Kosuke Imai, Michael Lingzhi Li:
Distributionally Robust Causal Inference with Observational Data. CoRR abs/2210.08326 (2022) - 2021
- [j183]Dimitris Bertsimas, Nishanth Mundru:
Sparse Convex Regression. INFORMS J. Comput. 33(1): 262-279 (2021) - [j182]Dimitris Bertsimas, Yee Sian Ng, Julia Yan:
Data-Driven Transit Network Design at Scale. Oper. Res. 69(4): 1118-1133 (2021) - [j181]Dimitris Bertsimas, Agni Orfanoudaki, Holly M. Wiberg:
Interpretable clustering: an optimization approach. Mach. Learn. 110(1): 89-138 (2021) - [j180]Dimitris Bertsimas, Agni Orfanoudaki, Colin Pawlowski:
Imputation of clinical covariates in time series. Mach. Learn. 110(1): 185-248 (2021) - [j179]Dimitris Bertsimas, Bartolomeo Stellato:
The voice of optimization. Mach. Learn. 110(2): 249-277 (2021) - [j178]Dimitris Bertsimas, Jean Pauphilet, Bart P. G. Van Parys:
Sparse classification: a scalable discrete optimization perspective. Mach. Learn. 110(11): 3177-3209 (2021) - [j177]Dimitris Bertsimas, Jack Dunn, Yuchen Wang:
Near-optimal Nonlinear Regression Trees. Oper. Res. Lett. 49(2): 201-206 (2021) - [j176]Dimitris Bertsimas, Ryan Cory-Wright, Jean Pauphilet:
A Unified Approach to Mixed-Integer Optimization Problems With Logical Constraints. SIAM J. Optim. 31(3): 2340-2367 (2021) - [j175]Dimitris Bertsimas, Dick den Hertog, Jean Pauphilet:
Probabilistic Guarantees in Robust Optimization. SIAM J. Optim. 31(4): 2893-2920 (2021) - [j174]Dimitris Bertsimas, Luca Mingardi, Bartolomeo Stellato:
Machine Learning for Real-Time Heart Disease Prediction. IEEE J. Biomed. Health Informatics 25(9): 3627-3637 (2021) - [i36]Dimitris Bertsimas, Vassilis Digalakis Jr., Michael Lingzhi Li, Omar Skali Lami:
Slowly Varying Regression under Sparsity. CoRR abs/2102.10773 (2021) - [i35]Dimitris Bertsimas, Arthur Delarue, Jean Pauphilet:
Prediction with Missing Data. CoRR abs/2104.03158 (2021) - [i34]Dimitris Bertsimas, Ryan Cory-Wright, Jean Pauphilet:
A new perspective on low-rank optimization. CoRR abs/2105.05947 (2021) - [i33]Dimitris Bertsimas, Agni Orfanoudaki:
Pricing Algorithmic Insurance. CoRR abs/2106.00839 (2021) - [i32]Hari Bandi, Dimitris Bertsimas:
The Price of Diversity. CoRR abs/2107.03900 (2021) - [i31]Dimitris Bertsimas, Ryan Cory-Wright, Nicholas A. G. Johnson:
Sparse Plus Low Rank Matrix Decomposition: A Discrete Optimization Approach. CoRR abs/2109.12701 (2021) - [i30]Dimitris Bertsimas, Léonard Boussioux, Kimberly Villalobos Carballo, Michael Lingzhi Li, Alex Paskov, Ivan S. Paskov:
Holistic Deep Learning. CoRR abs/2110.15829 (2021) - [i29]Donato Maragno, Holly M. Wiberg, Dimitris Bertsimas, S. Ilker Birbil, Dick den Hertog, Adejuyigbe O. Fajemisin:
Mixed-Integer Optimization with Constraint Learning. CoRR abs/2111.04469 (2021) - [i28]Dimitris Bertsimas, Xavier Boix, Kimberly Villalobos Carballo, Dick den Hertog:
A Robust Optimization Approach to Deep Learning. CoRR abs/2112.09279 (2021) - 2020
- [j173]Dimitris Bertsimas, Iain Dunning:
Relative Robust and Adaptive Optimization. INFORMS J. Comput. 32(2): 408-427 (2020) - [j172]Dimitris Bertsimas, Ying Daisy Zhuo:
Novel Target Discovery of Existing Therapies: Path to Personalized Cancer Therapy. INFORMS J. Optim. 2(1): 1-13 (2020) - [j171]Dimitris Bertsimas, Arthur Delarue, William Eger, John Hanlon, Sébastien Martin:
Bus Routing Optimization Helps Boston Public Schools Design Better Policies. INFORMS J. Appl. Anal. 50(1): 37-49 (2020) - [j170]Dimitris Bertsimas, Bradley Sturt:
Computation of Exact Bootstrap Confidence Intervals: Complexity and Deterministic Algorithms. Oper. Res. 68(3): 949-964 (2020) - [j169]Dimitris Bertsimas, Nathan Kallus:
From Predictive to Prescriptive Analytics. Manag. Sci. 66(3): 1025-1044 (2020) - [j168]Dimitris Bertsimas, Bart P. G. Van Parys:
Sparse hierarchical regression with polynomials. Mach. Learn. 109(5): 973-997 (2020) - [j167]Dimitris Bertsimas, Jourdain B. Lamperski, Jean Pauphilet:
Certifiably optimal sparse inverse covariance estimation. Math. Program. 184(1): 491-530 (2020) - [j166]Dimitris Bertsimas, Nataly Youssef:
Stochastic optimization in supply chain networks: averaging robust solutions. Optim. Lett. 14(4): 839-855 (2020) - [j165]Dimitris Bertsimas, Ryan Cory-Wright:
On polyhedral and second-order cone decompositions of semidefinite optimization problems. Oper. Res. Lett. 48(1): 78-85 (2020) - [j164]Dimitris Bertsimas, Michael Lingzhi Li:
Scalable holistic linear regression. Oper. Res. Lett. 48(3): 203-208 (2020) - [j163]Dimitris Bertsimas, Yeesian Ng, Julia Yan:
Joint Frequency-Setting and Pricing Optimization on Multimodal Transit Networks at Scale. Transp. Sci. 54(3): 839-853 (2020) - [c21]Abhishek Cauligi, Preston Culbertson, Bartolomeo Stellato, Dimitris Bertsimas, Mac Schwager, Marco Pavone:
Learning Mixed-Integer Convex Optimization Strategies for Robot Planning and Control. CDC 2020: 1698-1705 - [c20]Hari Bandi, Dimitris Bertsimas:
Optimizing Influenza Vaccine Composition: From Predictions to Prescriptions. MLHC 2020: 121-142 - [i27]Abhishek Cauligi, Preston Culbertson, Bartolomeo Stellato, Dimitris Bertsimas, Mac Schwager, Marco Pavone:
Learning Mixed-Integer Convex Optimization Strategies for Robot Planning and Control. CoRR abs/2004.03736 (2020) - [i26]Dimitris Bertsimas, Ryan Cory-Wright, Jean Pauphilet:
Solving Large-Scale Sparse PCA to Certifiable (Near) Optimality. CoRR abs/2005.05195 (2020) - [i25]Dimitris Bertsimas, Vassilis Digalakis Jr.:
The Backbone Method for Ultra-High Dimensional Sparse Machine Learning. CoRR abs/2006.06592 (2020) - [i24]Dimitris Bertsimas, Vassilis Digalakis Jr.:
Frequency Estimation in Data Streams: Learning the Optimal Hashing Scheme. CoRR abs/2007.09261 (2020) - [i23]Dimitris Bertsimas, Ryan Cory-Wright, Jean Pauphilet:
Mixed-Projection Conic Optimization: A New Paradigm for Modeling Rank Constraints. CoRR abs/2009.10395 (2020) - [i22]Léonard Boussioux, Cynthia Zeng, Théo Guénais, Dimitris Bertsimas:
Hurricane Forecasting: A Novel Multimodal Machine Learning Framework. CoRR abs/2011.06125 (2020) - [i21]Dimitris Bertsimas, Jack Dunn, Emma Gibson, Agni Orfanoudaki:
Optimal Survival Trees. CoRR abs/2012.04284 (2020)
2010 – 2019
- 2019
- [j162]Lauren Berk, Dimitris Bertsimas, Alexander M. Weinstein, Julia Yan:
Prescriptive analytics for human resource planning in the professional services industry. Eur. J. Oper. Res. 272(2): 636-641 (2019) - [j161]Dimitris Bertsimas, Patrick Jaillet, Nikita Korolko:
The K-server problem via a modern optimization lens. Eur. J. Oper. Res. 276(1): 65-78 (2019) - [j160]Dimitris Bertsimas, Yeesian Ng:
Robust and stochastic formulations for ambulance deployment and dispatch. Eur. J. Oper. Res. 279(2): 557-571 (2019) - [j159]Dimitris Bertsimas, Omid Nohadani:
Robust Maximum Likelihood Estimation. INFORMS J. Comput. 31(3): 445-458 (2019) - [j158]Dimitris Bertsimas:
From the Editor. INFORMS J. Optim. 1(1): 1 (2019) - [j157]Dimitris Bertsimas, Jack Dunn, Colin Pawlowski, Ying Daisy Zhuo:
Robust Classification. INFORMS J. Optim. 1(1): 2-34 (2019) - [j156]Dimitris Bertsimas:
Machine Learning and Optimization: Introduction to the Special Issue. INFORMS J. Optim. 1(2): 91 (2019) - [j155]Dimitris Bertsimas, Jack Dunn, Nishanth Mundru:
Optimal Prescriptive Trees. INFORMS J. Optim. 1(2): 164-183 (2019) - [j154]Dimitris Bertsimas:
Machine Learning and Optimization: Introduction to the Special Issue. INFORMS J. Optim. 1(3): 185-186 (2019) - [j153]Dimitris Bertsimas, Nikita Korolko, Alexander M. Weinstein:
Identifying Exceptional Responders in Randomized Trials: An Optimization Approach. INFORMS J. Optim. 1(3): 187-199 (2019) - [j152]Hari Bandi, Dimitris Bertsimas, Rahul Mazumder:
Learning a Mixture of Gaussians via Mixed-Integer Optimization. INFORMS J. Optim. 1(3): 221-240 (2019) - [j151]Dimitris Bertsimas:
Introduction to the Issue. INFORMS J. Optim. 1(4): 265-266 (2019) - [j150]