{"total":94,"rows":[{"id":"2103.16378","title":"End-to-End Constrained Optimization Learning: A Survey","created":"2021-03-30","cited_by_count":157,"area":null},{"id":"2307.13565","title":"Decision-Focused Learning: Foundations, State of the Art, Benchmark and Future Opportunities","created":"2023-07-25","cited_by_count":130,"area":null},{"id":"2106.01798","title":"Implicit MLE: Backpropagating Through Discrete Exponential Family Distributions","created":"2021-06-03","cited_by_count":98,"area":null},{"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":"2112.03609","title":"Decision-Focused Learning: Through the Lens of Learning to Rank","created":"2021-12-07","cited_by_count":62,"area":null},{"id":"2105.02343","title":"CombOptNet: Fit the Right NP-Hard Problem by Learning Integer Programming Constraints","created":"2021-05-05","cited_by_count":49,"area":null},{"id":"2106.04033","title":"Sample Complexity of Tree Search Configuration: Cutting Planes and Beyond","created":"2021-06-08","cited_by_count":33,"area":null},{"id":"2206.14234","title":"PyEPO: A PyTorch-based End-to-End Predict-then-Optimize Library for Linear and Integer Programming","created":"2022-06-28","cited_by_count":32,"area":null},{"id":"2205.15213","title":"Backpropagation through Combinatorial Algorithms: Identity with Projection Works","created":"2022-05-30","cited_by_count":29,"area":"lr"},{"id":"2207.13513","title":"Learning with Combinatorial Optimization Layers: a Probabilistic Approach","created":"2022-07-27","cited_by_count":29,"area":null},{"id":"2110.12351","title":"Integrated Conditional Estimation-Optimization","created":"2021-10-24","cited_by_count":25,"area":null},{"id":"2210.12547","title":"SurCo: Learning Linear Surrogates For Combinatorial Nonlinear Optimization Problems","created":"2022-10-22","cited_by_count":21,"area":null},{"id":"2305.16830","title":"Leaving the Nest: Going Beyond Local Loss Functions for Predict-Then-Optimize","created":"2023-05-26","cited_by_count":18,"area":null},{"id":"2307.08964","title":"Landscape Surrogate: Learning Decision Losses for Mathematical Optimization Under Partial Information","created":"2023-07-18","cited_by_count":18,"area":null},{"id":"2309.16965","title":"Controlling Continuous Relaxation for Combinatorial Optimization","created":"2023-09-29","cited_by_count":16,"area":null},{"id":"2106.10349","title":"The Perils of Learning Before Optimizing","created":"2021-06-18","cited_by_count":15,"area":null},{"id":"2106.07877","title":"Learning Revenue-Maximizing Auctions With Differentiable Matching","created":"2021-06-15","cited_by_count":14,"area":null},{"id":"2301.12047","title":"Backpropagation of Unrolled Solvers with Folded Optimization","created":"2023-01-28","cited_by_count":13,"area":null},{"id":"2306.13796","title":"On Learning Latent Models with Multi-Instance Weak Supervision","created":"2023-06-23","cited_by_count":13,"area":null},{"id":"2203.16067","title":"Decision-Focused Learning without Differentiable Optimization: Learning Locally Optimized Decision Losses","created":"2022-03-30","cited_by_count":12,"area":null},{"id":"2209.04862","title":"Adaptive Perturbation-Based Gradient Estimation for Discrete Latent Variable Models","created":"2022-09-11","cited_by_count":12,"area":null},{"id":"2102.07456","title":"Neuro-algorithmic Policies enable Fast Combinatorial Generalization","created":"2021-02-15","cited_by_count":11,"area":null},{"id":"2301.13395","title":"Differentiating Through Integer Linear Programs with Quadratic Regularization and Davis-Yin Splitting","created":"2023-01-31","cited_by_count":11,"area":null},{"id":"2307.05213","title":"Score Function Gradient Estimation to Widen the Applicability of Decision-Focused Learning","created":"2023-07-11","cited_by_count":11,"area":null},{"id":"2106.03188","title":"Combinatorial Optimization for Panoptic Segmentation: A Fully Differentiable Approach","created":"2021-06-06","cited_by_count":10,"area":null},{"id":"2411.19285","title":"BPQP: A Differentiable Convex Optimization Framework for Efficient End-to-End Learning","created":"2024-11-28","cited_by_count":10,"area":null},{"id":"2304.03674","title":"Machine Learning with Requirements: a Manifesto","created":"2023-04-07","cited_by_count":8,"area":null},{"id":"2311.07633","title":"Benchmarking PtO and PnO Methods in the Predictive Combinatorial Optimization Regime","created":"2023-11-13","cited_by_count":8,"area":null},{"id":"2312.07718","title":"CaVE: A Cone-Aligned Approach for Fast Predict-then-optimize with Binary Linear Programs","created":"2023-12-12","cited_by_count":8,"area":null},{"id":"2406.16571","title":"Differentiable Distributionally Robust Optimization Layers","created":"2024-06-24","cited_by_count":8,"area":null},{"id":"2410.11061","title":"Learning to Optimize for Mixed-Integer Non-linear Programming with Feasibility Guarantees","created":"2024-10-14","cited_by_count":8,"area":null},{"id":"2301.10074","title":"Explainable Data-Driven Optimization: From Context to Decision and Back Again","created":"2023-01-24","cited_by_count":7,"area":null},{"id":"2211.05116","title":"A Note on Task-Aware Loss via Reweighing Prediction Loss by Decision-Regret","created":"2022-11-09","cited_by_count":6,"area":null},{"id":"2212.01314","title":"On Solution Functions of Optimization: Universal Approximation and Covering Number Bounds","created":"2022-12-02","cited_by_count":6,"area":null},{"id":"2407.05920","title":"LPGD: A General Framework for Backpropagation through Embedded Optimization Layers","created":"2024-07-08","cited_by_count":6,"area":null},{"id":"2510.04951","title":"Feasibility-Aware Decision-Focused Learning for Predicting Parameters in the Constraints","created":"2025-10-06","cited_by_count":6,"area":null},{"id":"2210.09082","title":"A Solver-Free Framework for Scalable Learning in Neural ILP Architectures","created":"2022-10-17","cited_by_count":5,"area":null},{"id":"2310.04328","title":"Robust Losses for Decision-Focused Learning","created":"2023-10-06","cited_by_count":5,"area":null},{"id":"2311.13087","title":"Predict-Then-Optimize by Proxy: Learning Joint Models of Prediction and Optimization","created":"2023-11-22","cited_by_count":4,"area":null},{"id":"2504.07383","title":"PROPEL: Supervised and Reinforcement Learning for Large-Scale Supply Chain Planning","created":"2025-04-10","cited_by_count":4,"area":"deeprl"},{"id":"2210.08114","title":"QuAnt: Quantum Annealing with Learnt Couplings","created":"2022-10-13","cited_by_count":3,"area":null},{"id":"2307.16304","title":"You Shall Pass: Dealing with the Zero-Gradient Problem in Predict and Optimize for Convex Optimization","created":"2023-07-30","cited_by_count":3,"area":null},{"id":"2308.05889","title":"DF2: Distribution-Free Decision-Focused Learning","created":"2023-08-11","cited_by_count":3,"area":null},{"id":"2310.02442","title":"GenCO: Generating Diverse Designs with Combinatorial Constraints","created":"2023-10-03","cited_by_count":3,"area":null},{"id":"2312.14836","title":"Learning Lagrangian Multipliers for the Travelling Salesman Problem","created":"2023-12-22","cited_by_count":3,"area":null},{"id":"2402.02190","title":"Continuous Parallel Relaxation for Finding Diverse Solutions in Combinatorial Optimization Problems","created":"2024-02-03","cited_by_count":3,"area":null},{"id":"2505.11360","title":"Efficient End-to-End Learning for Decision-Making: A Meta-Optimization Approach","created":"2025-05-16","cited_by_count":3,"area":null},{"id":"2605.12754","title":"Constraint-Aware Flow Matching: Decision Aligned End-to-End Training for Constrained Sampling","created":"2026-05-12","cited_by_count":3,"area":"diffusion"},{"id":"2606.19587","title":"A Solver-Free Training Method for Predict-then-Optimize","created":"2026-06-17","cited_by_count":3,"area":null},{"id":"2102.02125","title":"Generative deep learning for decision making in gas networks","created":"2021-02-03","cited_by_count":2,"area":null},{"id":"2111.11358","title":"A Surrogate Objective Framework for Prediction+Optimization with Soft Constraints","created":"2021-11-22","cited_by_count":2,"area":null},{"id":"2208.13065","title":"Towards Improving Unit Commitment Economics: An Add-On Tailor for Renewable Energy and Reserve Predictions","created":"2022-08-27","cited_by_count":2,"area":null},{"id":"2302.14473","title":"Implicit Bilevel Optimization: Differentiating through Bilevel Optimization Programming","created":"2023-02-28","cited_by_count":2,"area":null},{"id":"2303.01543","title":"Decision-Oriented Learning with Differentiable Submodular Maximization for Vehicle Routing Problem","created":"2023-03-02","cited_by_count":2,"area":null},{"id":"2505.00671","title":"Multi-Constraint Safe Reinforcement Learning via Closed-form Solution for Log-Sum-Exp Approximation of Control Barrier Functions","created":"2025-05-01","cited_by_count":2,"area":"deeprl"},{"id":"2508.11365","title":"Minimizing Surrogate Losses for Decision-Focused Learning using Differentiable Optimization","created":"2025-08-15","cited_by_count":2,"area":null},{"id":"2202.11268","title":"Designing Decision Support Systems for Emergency Response: Challenges and Opportunities","created":"2022-02-23","cited_by_count":1,"area":null},{"id":"2205.10157","title":"Machine Learning for Combinatorial Optimisation of Partially-Specified Problems: Regret Minimisation as a Unifying Lens","created":"2022-05-20","cited_by_count":1,"area":null},{"id":"2312.17394","title":"Analyzing and Enhancing the Backward-Pass Convergence of Unrolled Optimization","created":"2023-12-28","cited_by_count":1,"area":null},{"id":"2401.05041","title":"Learning to Configure Mathematical Programming Solvers by Mathematical Programming","created":"2024-01-10","cited_by_count":1,"area":null},{"id":"2406.00779","title":"Differentiation of Multi-objective Data-driven Decision Pipeline","created":"2024-06-02","cited_by_count":1,"area":null},{"id":"2406.03082","title":"Learning Solutions of Stochastic Optimization Problems with Bayesian Neural Networks","created":"2024-06-05","cited_by_count":1,"area":null},{"id":"2411.16132","title":"TreeFormer: Single-view Plant Skeleton Estimation via Tree-constrained Graph Generation","created":"2024-11-25","cited_by_count":1,"area":null},{"id":"2601.21775","title":"Differentiable Knapsack and Top-k Operators via Dynamic Programming","created":"2026-01-29","cited_by_count":1,"area":null},{"id":"2601.22211","title":"Latent Spherical Flow Policy for Reinforcement Learning with Combinatorial Actions","created":"2026-01-29","cited_by_count":1,"area":"deeprl"},{"id":"2605.17773","title":"PlantPose: Universal Plant Skeleton Estimation via Tree-constrained Graph Generation","created":"2026-05-18","cited_by_count":1,"area":null},{"id":"2606.16790","title":"Decision-Weighted Flow Matching for Contextual Stochastic Optimization","created":"2026-06-15","cited_by_count":1,"area":"diffusion"},{"id":"2105.09136","title":"Periodic Freight Demand Estimation for Large-scale Tactical Planning","created":"2021-05-19","cited_by_count":0,"area":null},{"id":"2206.02015","title":"APES: Articulated Part Extraction from Sprite Sheets","created":"2022-06-04","cited_by_count":0,"area":null},{"id":"2206.07203","title":"Attributions Beyond Neural Networks: The Linear Program Case","created":"2022-06-14","cited_by_count":0,"area":null},{"id":"2212.01348","title":"Predict-and-Critic: Accelerated End-to-End Predictive Control for Cloud Computing through Reinforcement Learning","created":"2022-12-02","cited_by_count":0,"area":null},{"id":"2312.17640","title":"Decision-focused predictions via pessimistic bilevel optimization: complexity and algorithms","created":"2023-12-29","cited_by_count":0,"area":null},{"id":"2405.09004","title":"Improving Sequential Market Coordination via Value-oriented Renewable Energy Forecasting","created":"2024-05-15","cited_by_count":0,"area":null},{"id":"2405.18293","title":"CF-OPT: Counterfactual Explanations for Structured Prediction","created":"2024-05-28","cited_by_count":0,"area":null},{"id":"2410.17415","title":"End-to-End Optimization and Learning of Fair Court Schedules","created":"2024-10-22","cited_by_count":0,"area":null},{"id":"2411.03535","title":"The Differentiable Feasibility Pump","created":"2024-11-05","cited_by_count":0,"area":null},{"id":"2411.18432","title":"SPO-VCS: An End-to-End Smart Predict-then-Optimize Framework with Alternating Differentiation Method for Relocation Problems in Large-Scale Vehicle Crowd Sensing","created":"2024-11-27","cited_by_count":0,"area":null},{"id":"2503.05175","title":"Self-Supervised Penalty-Based Learning for Robust Constrained Optimization","created":"2025-03-07","cited_by_count":0,"area":null},{"id":"2503.18509","title":"Neuro-symbolic Weak Supervision: Theory and Semantics","created":"2025-03-24","cited_by_count":0,"area":null},{"id":"2507.00851","title":"Aligning Learning and Endogenous Decision-Making","created":"2025-07-01","cited_by_count":0,"area":null},{"id":"2508.20978","title":"Scaling Neuro-symbolic Problem Solving: Solver-Free Learning of Constraints and Objectives","created":"2025-08-28","cited_by_count":0,"area":null},{"id":"2510.21858","title":"Privacy-preserving Decision-focused Learning for Multi-energy Systems","created":"2025-10-23","cited_by_count":0,"area":null},{"id":"2511.08035","title":"From Sequential to Recursive: Enhancing Decision-Focused Learning with Bidirectional Feedback","created":"2025-11-11","cited_by_count":0,"area":null},{"id":"2512.11169","title":"CORL: Reinforcement Learning of MILP Policies Solved via Branch and Bound","created":"2025-12-11","cited_by_count":0,"area":"deeprl"},{"id":"2605.18005","title":"Scalable Decision-Focused Learning through Cost-Sensitive Regression","created":"2026-05-18","cited_by_count":0,"area":null},{"id":"2605.30456","title":"DisjunctiveNet: Neural Symbolic Learning via Differentiable Convexified Optimization Layers","created":"2026-05-28","cited_by_count":0,"area":null},{"id":"2606.02294","title":"Regularized Large Neighborhood Search","created":"2026-06-01","cited_by_count":0,"area":null},{"id":"2606.05649","title":"Diff2SP: Diffusion Models for Correlated Scenario Generation in Stochastic Programming","created":"2026-06-04","cited_by_count":0,"area":"diffusion"},{"id":"2606.10979","title":"Bellman-Taylor Score Decoding for Markov Decision Processes with State-Dependent Feasible Action Sets","created":"2026-06-09","cited_by_count":0,"area":null},{"id":"2606.21440","title":"Fusing Backdoors, Machine Learning, and Optimization for Large-Scale Parametric Mixed-Integer Programs","created":"2026-06-19","cited_by_count":0,"area":null},{"id":"2608.09042","title":"DualCert: A Solver for the Traveling Salesman Problem with Constraint-Coupled Learning","created":"2026-08-10","cited_by_count":0,"area":null},{"id":"2608.13079","title":"Constrained Graph Diffusion for Mixed Integer Optimization","created":"2026-08-13","cited_by_count":0,"area":null},{"id":"2608.19953","title":"Learning Early-to-Final Solution Consistency for MILP Acceleration","created":"2026-08-20","cited_by_count":0,"area":null},{"id":"2609.37065","title":"RL-PaO: Prediction as Action in Decision Making under Uncertainty","created":"2026-09-29","cited_by_count":0,"area":null}],"next_cursor":null}