Distributionally Robust Optimization

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DRO studies how to make predictions and decisions reliable when the distribution at deployment may differ from the observed data. Methods define ambiguity sets using tools such as Wasserstein distance, statistical divergences, or group-based reweighting, then solve the resulting worst-case optimization with dual formulations, gradient methods, or saddle-point algorithms. Applications include machine learning under subgroup and domain shifts, reinforcement learning, control, and decisions in areas such as healthcare and energy. A central challenge is balancing protection against distribution shift with computational cost and excessive conservatism, while choosing ambiguity sets that reflect real uncertainty and still support useful guarantees.

Latest papers

85 papers18 papers in the last four weeks, up 350% on the four weeks before. 0.1% of all new papers.

Relative Entropy-Bounded Ambiguous Chance Constraints for Robust Planning in Nonlinear Systems
Jul 18, 2026Trevor N. Wolf, Jay W. McMahonChance-Constrained Optimization Stochastic Optimal Control
Smead Department of Aerospace Engineering Sciences, University of Colorado Boulder, Boulder, CO 80303, USA
Approximate Relative Entropy Constraints for Nonlinear Covariance Steering Under Distribution Ambiguity
Jul 18, 2026Trevor N. Wolf, Jay W. McMahonDistributionally Robust Optimization
*Postdoctoral Associate, Department of Aerospace Engineering Sciences, University of Colorado Boulder, AAS Member. · †Associate Professor, University of Colorado Boulder, Department of Aerospace Engineering Sciences, and AAS Fellow.
Distributionally Robust and Safe Imitation Learning
Jul 15, 2026Ahmed Aboudonia, Naira HovakimyanDistribution Shift Robustness Distributionally Robust Optimization
University of California Berkeley, Berkeley, CA 94720, USA · University of Illinois Urbana-Champaign, Urbana, IL 61801, USA
Learning Predictive Ambiguity Sets for Decision-Focused Distributionally Robust Optimization
Jul 10, 2026Junjie GuoDistributionally Robust Optimization Decision-Focused Learning
Rutgers University
Decision-Focused Scenario Generation and Selection for Efficient and Robust Grid Dispatch
Jul 7, 2026Yangze Zhou, Yihong Zhou, Thomas Morstyn +1Distributionally Robust Optimization Decision-Focused Learning
Beyond the Performance Illusion: Structure-Aware Stratified Partitioning and Curriculum Distributionally Robust Optimization for Spatially Correlated Domains
Jul 2, 2026Prathamesh Patil, Arpit Jain, Aswanth KrishnanData Leakage Distributionally Robust Optimization
1QpiAI India Pvt. Ltd.
Distributionally Robust Listwise Preference Optimization
Jul 2, 2026Xudong Wu, Jian Qian, Pangpang Liu +2LLM Alignment Distributionally Robust Optimization
The University of Hong Kong · Hong Kong SAR · Yale University +3
Distributionally Robust Linear Regression With Block Lewis Weights
Jun 30, 2026Naren Sarayu Manoj, Kumar Kshitij PatelRobust Regression Group Distributionally Robust Optimization
TTIC · Institute for Foundations of Data Science, Yale University
A Distributionally Robust Framework for Learned Reconstructions in Inverse Problems
Jun 29, 2026Floor van Maarschalkerwaart, Subhadip Mukherjee, Christoph Brune +1Distribution Shift Robustness Distributionally Robust Optimization
University of Twente, Enschede, the Netherlands · IIT Kharagpur, Kharagpur, India
Distributionally Robust Set Representation Learning Under Inference-Time Element Corruption
May 28, 2026Yankai Chen, Hanrong Zhang, Bowei He +2Distribution Shift Robustness Representation Learning
MBZUAI · McGill University · University of Illinois Chicago
Conservative neural posterior estimation via distributionally robust training
May 27, 2026William Laplante, Yuga Hikida, Charita Dellaporta +2Simulation-Based Inference Neural Posterior Estimation
Department of Statistical Science, University College London, UK · The Alan Turing Institute, UK · Department of Computer Science, Aalto University, Finland
Choosing Online Experiment Designs under Interference in Ads, Recommendations, and Member-Experience Systems
May 24, 2026Prashant Shekhar, Caroline HowardDistributionally Robust Optimization
Department of Mathematics Embry-Riddle Aeronautical University Daytona Beach, FL, USA
Distributionally Robust Control via Stein Variational Inference for Contact-Rich Manipulation
May 18, 2026Hrishikesh Sathyanarayan, Victor Vantilborgh, Harish Ravichandar +2Contact-Rich Robotic Manipulation Robust Control
Yale University, New Haven, CT, USA · Ghent University, Belgium · Georgia Institute of Technology, Atlanta, GA, USA +1
Distributionally Robust Safety Under Arbitrary Uncertainties: A Safety Filtering Approach
May 13, 2026Daniel M. Cherenson, Haejoon Lee, Taekyung Kim +1Safety-Critical Control Distributionally Robust Optimization
Department of Robotics, University of Michigan, Ann Arbor, MI, USA
DuetFair: Coupling Inter- and Intra-Subgroup Robustness for Fair Medical Image Segmentation
May 11, 2026Yiqi Tian, Sangjoon Park, Bo Zeng +3Subgroup Robustness Healthcare
Center for Advanced Medical Computing and Analysis, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02114 · Department of Industrial Engineering, University of Pittsburgh, Pittsburgh, PA 15261 · Department of Radiation Oncology, College of Medicine, Yonsei University, Seoul, South Korea +2
Interactive Trajectory Planning with Learning-based Distributionally Robust Model Predictive Control and Markov Systems
May 8, 2026Erik Börve, Nikolce Murgovski, Morteza Haghir Chehreghani +1Distributionally Robust Optimization Model Predictive Control
Chalmers University of Technology, Chalmersgatan 4, 412 96 Göteborg, Sweden · Volvo Group Trucks Technology, Gropegårdsgatan 2, 417 15 Göteborg, Sweden
Ensemble Distributionally Robust Bayesian Optimisation with Continuous Context
May 8, 2026Tigran Ramazyan, Denis DerkachBayesian Optimization Distributionally Robust Optimization
Faculty of Computer Science, HSE University, Pokrovsky Boulevard 11, Moscow, 109028, Moscow, Russia.
Distributionally-Robust Learning to Optimize
May 7, 2026Vinit Ranjan, Jisun Park, Bartolomeo StellatoLearning to Optimize Distributionally Robust Optimization
Department of Operations Research and Financial Engineering, Princeton University. · Department of Operations Research and Financial Engineering, Princeton University, and Research Institute of Mathematics, Seoul National University. · Research Institute of Mathematics, Seoul National University.
From Dual Tracking to Clipping: Provably Faster Distributionally Robust Multi-Objective Optimization
May 7, 2026Yufeng Yang, Fangning Zhuo, Ziyi Chen +2Gradient Clipping Gradient Descent
Texas A&M University · A*STAR · University of Maryland
Information Theoretic Adversarial Training of Large Language Models
May 6, 2026Yiwei Zhang, Jeremiah Birrell, Reza Ebrahimi +3Adversarial Training LLM Alignment
Purdue University · West Lafayette, IN 47907, USA · Texas State University +5
Quantile Geometry Regularization for Distributional Reinforcement Learning
May 5, 2026Zhaofan Zhang, Minghao Yang, Rufeng Chen +2Distributional RL Quantile Regression
Information Hub, AI Thrust Hong Kong University of Science and Technology (Guangzhou) Guangzhou, Guangdong, China
Wasserstein Distributionally Robust Regret Optimization for Reinforcement Learning from Human Feedback
Apr 30, 2026Yikai Wang, Shang Liu, Jose BlanchetReward Over-Optimization Regret Minimization in RL
Department of Statistics and Operations Research, University of North Carolina · Imperial Business School, Imperial College London · Department of Management Science and Engineering, Stanford University
Sampler-Robust Optimization under Generative Models
Apr 30, 2026Ziwei Zhang, Jonathan Yu-Meng LiDistribution Shift Robustness Distributionally Robust Optimization
Telfer School of Management University of Ottawa
A Distributionally Robust Reinforcement Learning Framework for Constrained Urban EV Dispatch
Apr 28, 2026An Nguyen, Hoang Nguyen, Phuong Le +3Electric Vehicle Charging Constrained RL
College of Engineering and Computer Science, VinUniversity, Hanoi, Vietnam · Center for Environmental Intelligence, VinUniversity, Hanoi, Vietnam
Robust Out-of-Distribution Stochastic Optimization
Apr 22, 2026Xianyu Li, Huan Xu, Xiaolin Huang +1Stochastic Optimization OOD Generalization
Department of Automation, Tsinghua University · Antai College of Economics & Management, Shanghai Jiao Tong University · Institute of Image Processing and Pattern Recognition, Shanghai Jiao Tong University
Wasserstein Distributionally Robust Risk-Sensitive Estimation via Conditional Value-at-Risk
Apr 20, 2026Feras Al Taha, Eilyan BitarDistributionally Robust Optimization Wasserstein Distributionally Robust Optimization
School of Electrical and Computer Engineering, Cornell University, Ithaca, NY 14853 USA
STaR-DRO: Stateful Tsallis Reweighting for Group-Robust Structured Prediction
Apr 9, 2026Samah Fodeh, Ganesh Puthiaraju, Elyas Irankhah +5Structured Prediction Distributionally Robust Optimization
Yale University, New Haven, CT, USA. · Medical Oncology, Yale School of Medicine, New Haven, CT, USA.
Robust Learning of Heterogeneous Dynamic Systems
Apr 7, 2026Shuoxun Xu, Zijian Guo, Brooke R. Staveland +2Dynamical Systems Robust Estimation
University of California at Berkeley · Zhejiang University · University of California at San Francisco
Reproducibility study on how to find Spurious Correlations, Shortcut Learning, Clever Hans or Group-Distributional non-robustness and how to fix them
Apr 6, 2026Ole Delzer, Sidney BenderGroup Distributionally Robust Optimization Spurious Correlation Robustness
Machine Learning Group Technische Universität Berlin
Generative models for decision-making under distributional shift
Apr 6, 2026Xiuyuan Cheng, Yunqin Zhu, Yao XieDecision-Making under Uncertainty Distribution Shift Robustness
Department of Mathematics, Duke University, Durham, NC, USA · H. Milton Stewart School of Industrial and Systems Engineering, Georgia Institute of Technology, Atlanta, GA, USA

Jul 18, 2026J/K move · Enter open · S save

Relative Entropy-Bounded Ambiguous Chance Constraints for Robust Planning in Nonlinear Systems

Trevor N. Wolf, Jay W. McMahon

Smead Department of Aerospace Engineering Sciences, University of Colorado Boulder, Boulder, CO 80303, USA

Chance-Constrained Optimization Stochastic Optimal Control Distributionally Robust Optimization

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We consider defining risk probability in stochastic control problems under distribution ambiguity. Current approaches for chance-constrained control typically assume that the true state distribution is known and Gaussian distributed. These assumptions are not amenable to many real-world engineering applications where system dynamics are nonlinear and only approximately modeled. In this work, we define a distribution ambiguity set and, with a variational expression for exponential integrals, bound the expected risk value under an unknown distribution that resides within a relative entropy distance of a nominal Gaussian reference distribution. Our bound recovers the reference risk value in the zero-divergence limit. A method is presented to determine the relative entropy distance defining the ambiguity set that is a function of the reference covariance evolution and second-order dynamical truncation errors. The resulting contributions provide a framework for handling distributional ambiguity in nonlinear covariance steering problems. A stochastic spacecraft guidance example is presented to demonstrate our contributions.