Decision Making

Omniprediction with Long-Term Constraints COLT 2026 Robust Decision-Focused Learning via Worst-Case Regret Minimization UAI 2026 Decision from Suboptimal Classifiers: Excess Risk Pre- and Post-Calibration AISTATS 2025 DF$^2$: Distribution-Free Decision-Focused Learning UAI 2025 Learning the Distribution Map in Reverse Causal Performative Prediction AISTATS 2025 Prior-Dependent Allocations for Bayesian Fixed-Budget Best-Arm Identification in Structured Bandits AISTATS 2025 Risk-sensitive Bandits: Arm Mixture Optimality and Regret-efficient Algorithms AISTATS 2025 A Discretization Framework for Robust Contextual Stochastic Optimization ICLR 2024 Enhancing Patient Recruitment Response in Clinical Trials: an Adaptive Learning Framework UAI 2024 Group Fairness in Predict-Then-Optimize Settings for Restless Bandits UAI 2024 On the Actionability of Outcome Prediction AAAI 2024 Variance-aware Regret Bounds for Stochastic Contextual Dueling Bandits ICLR 2024 Modeling Human Trust and Reliance in AI-Assisted Decision Making: A Markovian Approach AAAI 2023 Moral Machine or Tyranny of the Majority? AAAI 2023 Branch & Learn for Recursively and Iteratively Solvable Problems in Predict+Optimize NeurIPS 2022 Comparing Distributions by Measuring Differences that Affect Decision Making ICLR 2022 Identifying near-optimal decisions in linear-in-parameter bandit models with continuous decision sets UAI 2022 Parametrically Retargetable Decision-Makers Tend To Seek Power NeurIPS 2022 A Universal 2-state n-action Adaptive Management Solver AAAI 2021 Online Learning from Optimal Actions COLT 2021 Risk Bounds and Calibration for a Smart Predict-then-Optimize Method NeurIPS 2021 Decision-Making with Auto-Encoding Variational Bayes NeurIPS 2020 Generalization Bounds in the Predict-then-Optimize Framework NeurIPS 2019 Balancing Suspense and Surprise: Timely Decision Making with Endogenous Information Acquisition NeurIPS 2016 Pull the Plug? Predicting If Computers or Humans Should Segment Images CVPR 2016