Tutorials

Getting Started

• Overview
  • Data Module
  • Synthetic Data Generation
  • Model Module
  • Reference

Linear Models

• Linear DRO Overview
  • \(f\)-divergence DRO
  • Wasserstein DRO
  • Group DRO
  • MMD-DRO
  • Bayesian (Parametric) DRO
  • Hybrid-distance DRO
• Linear f-divergence DRO
  • Standard (Generalized)
  • Partial DRO
  • Reference
• Linear Wasserstein DRO
  • Standard Version
  • Robust Satisficing Version
  • Reference
• Linear Group DRO
  • Formulation
  • Defining groups
  • Hyperparameters
  • Fitting and diagnostics
  • Practical guidance
  • Reference
• Linear MMD-DRO
  • Hyperparameters
  • Reference
• Linear Bayesian DRO
  • Hyperparameters
  • Reference
• Linear Hybrid-Distance DRO
  • Sinkhorn-DRO
  • Holistic-DRO
  • MOT-DRO
  • Outlier-Robust Wasserstein DRO
  • Reference

Neural Models

• Neural DRO Overview
  • \(\chi^2\)-DRO and CVaR-DRO
  • Wasserstein DRO
  • Holistic Robust DRO
  • Sinkhorn DRO
  • Group DRO
• Neural DRO Robustness Certificates
  • Certificate Guarantees
  • Wasserstein DRO
  • \(\chi^2\)-DRO
  • CVaR-DRO
  • Examples
  • Reference

Tree Models

• Tree DRO
  • Formulation
  • Objective and booster configuration
  • Fitting and diagnostics

Personalization

• Personalization
  • Linear (Convex) DRO Methods
  • NN-Based DRO Methods
  • Tree-Based DRO Methods