mlsanityData to 14 Oct 2026

Conformal Contextual Robust Optimization

arXiv 2310.10003 ↗First posted 16 Oct 2023stat.ME cs.LG stat.MLcited by 25

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Abstract (arXiv)

Data-driven approaches to predict-then-optimize decision-making problems seek to mitigate the risk of uncertainty region misspecification in safety-critical settings. Current approaches, however, suffer from considering overly conservative uncertainty regions, often resulting in suboptimal decisionmaking. To this end, we propose Conformal-Predict-Then-Optimize (CPO), a framework for leveraging highly informative, nonconvex conformal prediction regions over high-dimensional spaces based on conditional generative models, which have the desired distribution-free coverage guarantees. Despite guaranteeing robustness, such black-box optimization procedures alone inspire little confidence owing to the lack of explanation of why a particular decision was found to be optimal. We, therefore, augment CPO to additionally provide semantically meaningful visual summaries of the uncertainty regions to give qualitative intuition for the optimal decision. We highlight the CPO framework by demonstrating results on a suite of simulation-based inference benchmark tasks and a vehicle routing task based on probabilistic weather prediction.

Key facts. Cited by 25 papers in the map (data through 14 Oct 2026). Builds on 33 of its 73 references that are in the map. First posted on arXiv 16 Oct 2023.

Builds on

33 of 73 references.

References · 33

  1. 2014Adam: A Method for Stochastic Optimizationcited by 37,240
  2. 2019PyTorch: An Imperative Style, High-Performance Deep Learning Librarycited by 20,305
  3. 2017Towards A Rigorous Science of Interpretable Machine Learningcited by 1,416
  4. 2021A Gentle Introduction to Conformal Prediction and Distribution-Free Uncertainty Quantificationcited by 792
  5. 2019Neural Spline Flowscited by 596
  6. 2017Smart "Predict, then Optimize"cited by 339
  7. 2017Deep Learning for Precipitation Nowcasting: A Benchmark and A New Modelcited by 182
  8. 2021Benchmarking Simulation-Based Inferencecited by 162
  9. 2016OSMnx: New Methods for Acquiring, Constructing, Analyzing, and Visualizing Complex Street Networkscited by 110
  10. 2022Image-to-Image Regression with Distribution-Free Uncertainty Quantification and Applications in Imagingcited by 107
  11. 2022GFlowNets and variational inferencecited by 106
  12. 2013Data-Driven Robust Optimizationcited by 85
21 more
  1. 2023A Survey of Contextual Optimization Methods for Decision Making under Uncertaintycited by 82
  2. 2021Conformal Prediction using Conditional Histogramscited by 77
  3. 2019A comparison of some conformal quantile regression methodscited by 76
  4. 2020CD-split and HPD-split: efficient conformal regions in high dimensionscited by 76
  5. 2019Machine Learning for Precipitation Nowcasting from Radar Imagescited by 56
  6. 2023Latent diffusion models for generative precipitation nowcasting with accurate uncertainty quantificationcited by 56
  7. 2022Conformal Prediction Under Feedback Covariate Shift for Biomolecular Designcited by 54
  8. 2020Decision Trees for Decision-Making under the Predict-then-Optimize Frameworkcited by 53
  9. 2021Calibrated Multiple-Output Quantile Regression with Representation Learningcited by 50
  10. 2021Conformal Uncertainty Sets for Robust Optimizationcited by 49
  11. 2022Probabilistic Conformal Prediction Using Conditional Random Samplescited by 47
  12. 2023GFlowNet-EM for learning compositional latent variable modelscited by 40
  13. 2022Conffusion: Confidence Intervals for Diffusion Modelscited by 33
  14. 2023Principal Uncertainty Quantification with Spatial Correlation for Image Restoration Problemscited by 28
  15. 2020Valid model-free spatial predictioncited by 19
  16. 2023Predict-then-Calibrate: A New Perspective of Robust Contextual LPcited by 17
  17. 2018Forward Amortized Inference for Likelihood-Free Variational Marginalizationcited by 14
  18. 2023Physics Constrained Motion Prediction with Uncertainty Quantificationcited by 11
  19. 2023Variational Inference with Coverage Guarantees in Simulation-Based Inferencecited by 5
  20. 2018A data-driven robust optimization approach to scenario-based stochastic model predictive controlcited by 4
  21. 2021Data-Driven Robust Optimization Using Scenario-Induced Uncertainty Setscited by 2

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Cited by year (2026 to 14 Oct)

Citing papers per year: 2024: 6; 2025: 10; 2026: 9.

25 papers.

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  1. 2025Decision Theoretic Foundations for Conformal Prediction: Optimal Uncertainty Quantification for Risk-Averse Agentscited by 40
  2. 2025Gen-DFL: Decision-Focused Generative Learning for Robust Decision Makingcited by 18
  3. 2024End-to-end Conditional Robust Optimizationcited by 17
  4. 2024End-to-End Conformal Calibration for Optimization Under Uncertaintycited by 15
  5. 2024Utility-Directed Conformal Prediction: A Decision-Aware Framework for Actionable Uncertainty Quantificationcited by 13
  6. 2024Conformal Prediction for Ensembles: Improving Efficiency via Score-Based Aggregationcited by 9
  7. 2024Conformalized Interval Arithmetic with Symmetric Calibrationcited by 8
  8. 2025Volume-Sorted Prediction Set: Efficient Conformal Prediction for Multi-Target Regressioncited by 6
  9. 2025Enhanced Route Planning with Calibrated Uncertainty Setcited by 5
  10. 2025Calibrating Decision Robustness via Inverse Conformal Risk Controlcited by 4
  11. 2026Optimal Decision-Making Based on Prediction Setscited by 4
  12. 2024A Conformal Approach to Feature-based Newsvendor under Model Misspecificationcited by 3
13 more
  1. 2025Enhancing Electricity-System Resilience with Adaptive Robust Optimization and Conformal Uncertainty Characterizationcited by 3
  2. 2025Conformalized Decision Risk Assessmentcited by 3
  3. 2025Smart Surrogate Losses for Contextual Stochastic Linear Optimization with Robust Constraintscited by 2
  4. 2026Conformal Risk-Averse Decision Making with Action Conditional Guaranteecited by 2
  5. 2025Conformal Mixed-Integer Constraint Learning with Feasibility Guaranteescited by 1
  6. 2026Risk-Controlled Post-Processing of Decision Policiescited by 1
  7. 2026Learning Polyhedral Conformal Sets for Robust Optimizationcited by 1
  8. 2026Conformal-DRO: Distributionally Robust Optimization with Conformalized Ambiguity Setcited by 1
  9. 2025Adaptive Conformal Prediction for Quantum Machine Learningcited by 0
  10. 2026Distribution-Free Robust Predict-Then-Optimize in Function Spacescited by 0
  11. 2026Contextual Preference Distribution Learningcited by 0
  12. 2026Smart predict-then-robustly-optimizecited by 0
  13. 2026Counterfactual Online Conformal Prediction Under Adaptive Loggingcited by 0