Data-Driven Optimization: A Reproducing Kernel Hilbert Space Approach
From MaRDI portal
Publication:5031022
DOI10.1287/opre.2020.2069zbMath1485.90131OpenAlexW3134561541WikidataQ120689919 ScholiaQ120689919MaRDI QIDQ5031022
Nihal Koduri, Dimitris J. Bertsimas
Publication date: 18 February 2022
Published in: Operations Research (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1287/opre.2020.2069
optimizationoptimalityregressionreproducing kernel Hilbert spacedata-driven optimizationprescriptive analytics
Nonlinear programming (90C30) Approximation methods and heuristics in mathematical programming (90C59)
Related Items
Dynamic optimization with side information ⋮ The role of optimization in some recent advances in data-driven decision-making ⋮ A deficiency of prescriptive analytics -- no perfect predicted value or predicted distribution exists
Cites Work
- Tikhonov, Ivanov and Morozov regularization for support vector machine learning
- Data-driven robust optimization
- On the mathematical foundations of learning
- The Sample Average Approximation Method for Stochastic Discrete Optimization
- Introduction to Stochastic Programming
- Distributionally Robust Optimization Under Moment Uncertainty with Application to Data-Driven Problems
- Theory and Applications of Robust Optimization
- 10.1162/153244302760200704
- The Big Data Newsvendor: Practical Insights from Machine Learning
- Theory of Reproducing Kernels
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item