{"total":43,"rows":[{"id":"2306.10374","title":"A Survey of Contextual Optimization Methods for Decision Making under Uncertainty","created":"2023-06-17","cited_by_count":82,"area":null},{"id":"2502.02561","title":"Decision Theoretic Foundations for Conformal Prediction: Optimal Uncertainty Quantification for Risk-Averse Agents","created":"2025-02-04","cited_by_count":40,"area":null},{"id":"2501.05673","title":"Network Diffuser for Placing-Scheduling Service Function Chains with Inverse Demonstration","created":"2025-01-10","cited_by_count":11,"area":null},{"id":"2305.07730","title":"Learning in Inverse Optimization: Incenter Cost, Augmented Suboptimality Loss, and Algorithms","created":"2023-05-12","cited_by_count":10,"area":null},{"id":"2501.14349","title":"Online Inverse Linear Optimization: Efficient Logarithmic-Regret Algorithm, Robustness to Suboptimality, and Lower Bound","created":"2025-01-24","cited_by_count":9,"area":null},{"id":"2506.01502","title":"Learning of Population Dynamics: Inverse Optimization Meets JKO Scheme","created":"2025-06-02","cited_by_count":9,"area":null},{"id":"2501.13648","title":"Revisiting Online Learning Approach to Inverse Linear Optimization: A Fenchel$-$Young Loss Perspective and Gap-Dependent Regret Analysis","created":"2025-01-23","cited_by_count":8,"area":null},{"id":"2602.01682","title":"Finite and Corruption-Robust Regret Bounds in Online Inverse Linear Optimization under M-Convex Action Sets","created":"2026-02-02","cited_by_count":8,"area":null},{"id":"2603.20826","title":"Simple Projection-Free Algorithm for Contextual Recommendation with Logarithmic Regret and Robustness","created":"2026-03-21","cited_by_count":6,"area":null},{"id":"2605.08866","title":"Tight Generalization Bounds for Noiseless Inverse Optimization","created":"2026-05-09","cited_by_count":6,"area":null},{"id":"2307.07357","title":"Inverse Optimization for Routing Problems","created":"2023-07-14","cited_by_count":5,"area":null},{"id":"2308.12161","title":"Data-driven decision-focused surrogate modeling","created":"2023-08-23","cited_by_count":4,"area":null},{"id":"2405.14273","title":"Exact Solution to Data-Driven Inverse Optimization of MILPs in Finite Time via Gradient-Based Methods","created":"2024-05-23","cited_by_count":4,"area":null},{"id":"2602.00989","title":"Optimal Decision-Making Based on Prediction Sets","created":"2026-02-01","cited_by_count":4,"area":null},{"id":"2402.17890","title":"From Inverse Optimization to Feasibility to ERM","created":"2024-02-27","cited_by_count":3,"area":null},{"id":"2405.15431","title":"Counterfactual Explanations for Linear Optimization","created":"2024-05-24","cited_by_count":3,"area":null},{"id":"2405.17875","title":"BO4IO: A Bayesian optimization approach to inverse optimization with uncertainty quantification","created":"2024-05-28","cited_by_count":3,"area":null},{"id":"2410.23952","title":"Scalable Kernel Inverse Optimization","created":"2024-10-31","cited_by_count":3,"area":null},{"id":"2502.14160","title":"Efficient Inverse Multiagent Learning","created":"2025-02-20","cited_by_count":3,"area":null},{"id":"2505.13243","title":"Conformalized Decision Risk Assessment","created":"2025-05-19","cited_by_count":3,"area":null},{"id":"2609.13440","title":"Efficient Online Inverse Optimization with $O(d)$ Regret","created":"2026-09-11","cited_by_count":3,"area":null},{"id":"2402.04646","title":"Block Sparse Bayesian Learning: A Diversified Scheme","created":"2024-02-07","cited_by_count":2,"area":null},{"id":"2510.04455","title":"Inverse Mixed-Integer Programming: Learning Constraints then Objective Functions","created":"2025-10-06","cited_by_count":2,"area":null},{"id":"2606.05551","title":"Conformal Risk-Averse Decision Making with Action Conditional Guarantee","created":"2026-06-04","cited_by_count":2,"area":null},{"id":"2606.29582","title":"Bilevel Optimization for Neural Architecture Search","created":"2026-06-28","cited_by_count":2,"area":null},{"id":"2607.22263","title":"Explicit Iteration Complexity of Exact Data-Driven Inverse Optimization for Integer Linear Programs","created":"2026-07-24","cited_by_count":2,"area":null},{"id":"2609.26978","title":"Tight Regret Bound for Online Inverse Linear Optimization via Multiscale Matrix Weights","created":"2026-09-22","cited_by_count":2,"area":null},{"id":"2405.14090","title":"Solving 0-1 Integer Programs with Unknown Knapsack Constraints Using Membership Oracles","created":"2024-05-23","cited_by_count":1,"area":null},{"id":"2410.02774","title":"Estimating the Unobservable Components of Electricity Demand Response with Inverse Optimization","created":"2024-09-17","cited_by_count":1,"area":null},{"id":"2506.01869","title":"Frugal Machine Learning for Energy-efficient, and Resource-aware Artificial Intelligence","created":"2025-06-02","cited_by_count":1,"area":null},{"id":"2410.02628","title":"Inverse Entropic Optimal Transport Solves Semi-supervised Learning via Data Likelihood Maximization","created":"2024-10-03","cited_by_count":0,"area":null},{"id":"2502.16120","title":"A Fenchel-Young Loss Approach to Data-Driven Inverse Optimization","created":"2025-02-22","cited_by_count":0,"area":null},{"id":"2503.11435","title":"Preference Elicitation for Multi-objective Combinatorial Optimization with Active Learning and Maximum Likelihood Estimation","created":"2025-03-14","cited_by_count":0,"area":null},{"id":"2511.05640","title":"Blind Inverse Game Theory: Jointly Decoding Rewards and Rationality in Entropy-Regularized Competitive Games","created":"2025-11-07","cited_by_count":0,"area":null},{"id":"2602.20152","title":"Behavior Learning (BL): Learning Hierarchical Optimization Structures from Data","created":"2026-02-23","cited_by_count":0,"area":null},{"id":"2603.17139","title":"Contextual Preference Distribution Learning","created":"2026-03-17","cited_by_count":0,"area":null},{"id":"2606.28764","title":"Hierarchical Decision Making with Structured Policies: A Principled Design via Inverse Optimization","created":"2026-06-27","cited_by_count":0,"area":null},{"id":"2607.09752","title":"Data-Driven Forward and Inverse Modeling of V-Beam Thermal Sensors","created":"2026-07-04","cited_by_count":0,"area":null},{"id":"2607.23480","title":"A Multi-stage Constrained Optimization Framework for Data-driven Problems","created":"2026-07-26","cited_by_count":0,"area":null},{"id":"2608.07398","title":"Uncovering expert objectives in production planning via inverse optimization: An industrial case study","created":"2026-08-07","cited_by_count":0,"area":null},{"id":"2608.15124","title":"Decision-Driven Regularization: A Blended Model for Learning and Optimization","created":"2026-08-15","cited_by_count":0,"area":null},{"id":"2608.26051","title":"The Value of Human Expertise","created":"2026-08-26","cited_by_count":0,"area":null},{"id":"2609.38434","title":"TACIT: Optimization Models that Learn from Their Mistakes","created":"2026-09-29","cited_by_count":0,"area":null}],"next_cursor":null}