Differentiable Optimization

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6 papers in the last four weeks, against 2 the four weeks before. 0.1% of all new papers.

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Latest papers 58

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Decision-Focused Learning in MDPs: An Occupancy Measure Approach
Oct 6, 2026Zihao Zhao, Ashwath K. Karunakaram, Ali Eshragh +2Markov Decision Processes Decision-Focused Learning
Georgia Institute of Technology, Atlanta, GA · Johns Hopkins Carey Business School, Washington, DC · International Computer Science Institute, Berkeley, CA
Same Loss, Different Gradients
Sep 30, 2026Ningkang Peng, Xiaoqian Peng, Yifan He +4Automatic Differentiation Differentiable Optimization
Nanjing Normal University · Nanjing University of Chinese Medicine
On the Numerical Reliability of Differentiable Physics-Based Optimization for Robotic Material Manipulation
Sep 28, 2026Xintong Yang, Minglun Wei, Yu-Kun Lai +1Robot Dynamics Identification Material Point Method
School of Engineering, Cardiff University, Cardiff, United Kingdom · School of Computer Science and Informatics, Cardiff University, Cardiff, United Kingdom · College of Mechanical and Electrical Engineering, Hohai University, China
dOPT: Differentiating Conic Optimization via Geometric Reduction
Sep 27, 2026Fengyu Yang, Connor W. Magoon, Tyler Watts +1Differentiable Programming Constrained Optimization
Department of Mathematics University of North Carolina at Chapel Hill
lapanda: A Matrix-Free Differentiable Solver for Nonconvex Constrained Optimization Layers
Sep 27, 2026Yuankun Chen, Zifei Nie, Kangyu Lin +2Differentiable Programming Nonconvex Optimization
School of Artificial Intelligence, Jilin University, China · Graduate School of Informatics, Kyoto University, JPN · Department of Civil and Systems Engineering, Johns Hopkins University, USA
Customizable and Jointly Optimized Route Planning: A Deep Architecture Enabling Differentiable Shortest-Path Search
Sep 17, 2026Rui Zhao, Chao Chen, Longfei Xu +4Graph-Based Planning Differentiable Optimization
Alibaba Group Beijing, China · Alibaba Group Hangzhou, China
HGTO: A Unified Graph-Based Physics-Informed Formulation for Structural Topology Optimization
Sep 14, 2026Kangzheng Liu, Uday Kumar Punna, Leixin MaTopology Optimization Structural Mechanics
School for Engineering of Matter, Transport and Energy, Arizona State University, Tempe, 85287, AZ, USA
Differentiable Hybrid Modelling for Learning and Optimising Chemical Transport Processes from Experimental Data
Sep 3, 2026Arthur Jessop, Mohammed Alsubeihi, Ben Moseley +1Differentiable Physics Differentiable Optimization
Department of Chemical Engineering, The University of Manchester, Manchester, M13 9PL, United Kingdom. · Department of Earth Science and Engineering, Imperial College London, South Kensington, SW7 2BX, United Kingdom. · I-X Centre for AI in Science, Imperial College London, South Kensington, SW7 2BX, United Kingdom.
Differentiable Electricity-Market Clearing for Gradient-Based Planning
Sep 2, 2026Luca Mungo, Maarten P. Scholl, Arnau Quera-BofarullDifferentiable Optimization
Macrocosm Inc. · Institute for New Economic Thinking, University of Oxford
Hölder Signed Distance: A Differentiable, Signed, Parallelizable Metric for Robotics
Aug 7, 2026Felipe Bartelt, Ali Umut Kaypak, Anthony Tzes +3Signed Distance Functions Differentiable Optimization
Fast LapSum: Exact Differentiable Top- $k$ at Million Scale
Aug 7, 2026Jakub Antczak, Joanna Wojciechowicz, Kamil Książek +3Differentiable Programming Differentiable Optimization
Wrocław University of Science and Technology, Wrocław, Poland. · Faculty of Mathematics and Computer Science, Jagiellonian University, Kraków, Poland.
Differentiating Through Dual Prices: End-to-End Policy Learning Under Capacity Constraints
Aug 5, 2026Mohammadsaeed Haghi, Mahdi Salmani, Nima KelidariConstrained Optimization Differentiable Optimization
University of Southern California
Hard Constraints, Smooth Gradients: Learning Feasible Inventory Policies via Differentiable Projection
Aug 3, 2026Patrick Helm, Jan-Niklas Doerr, Joren Gijsbrechts +1Inventory Control Constrained RL
TUM School of Management, Technical University of Munich · Esade, Ramon Llull University · Munich Data Science Institute (MDSI), Technical University of Munich
Amortising Trajectory Optimisation for Residual MPC via Implicit Contact Differentiation
Jul 27, 2026Daniel Layeghi, Thomas Corbères, Calum Arnott +4Trajectory Optimization Automatic Differentiation
School of Informatics, University of Edinburgh, Scotland.
Smooth Learning with Hard Constraints via Legendre-Regularized Policies
Jul 27, 2026Zikun Lin, Rui Chen, Yijie WangDecision-Focused Learning Constrained Optimization
Department of Systems Engineering and Engineering Management, The Chinese University of Hong Kong, Hong Kong, China. · School of Data Science, The Chinese University of Hong Kong, Shenzhen, Guangdong, China. · School of Economics and Management, Tongji University, Shanghai, China.
End-to-End Learning of Safe Optimal Feedback Control in High Dimensions with Control Barrier Function Layers
Jul 22, 2026Xingjian Li, Kelvin Kan, Deepanshu Verma +3Safety-Critical Control Control Barrier Functions
UT Austin · UCLA · Clemson University +1
Widest-Path Reachability Fields for Connectivity-Preserving Slender Structure Segmentation
Jul 8, 2026Youcheng Zong, Runda Jia, Minxuan Hu +2Image Segmentation Topology-Preserving Image Segmentation
College of Information Science and Engineering, Northeastern University, Shenyang 110004, China · Changsha Stomatological Hospital, Changsha 410005, China
Directly Optimizing Mean Demographic Parity for Nonlinear Regression
Jul 6, 2026Ieva Petrulionyte, Julien Mairal, Michael ArbelAlgorithmic Fairness Group Fairness
Univ. Grenoble Alpes, Inria, CNRS, Grenoble INP, LJK, 38000 Grenoble, France
Smooth $\%$ MinMax: A Differentiable Relaxation for Codon Harmonization
Jul 4, 2026Yoonho Jeong, Hyunwoo Choi, Ryan Fernandez Medina Hariri +3Differentiable Optimization
Department of Chemistry, KAIST, Daejeon 34141, Korea. · School of Chemistry and Chemical Engineering, Highfield Campus, University of Southampton, Southampton SO17 1BJ, United Kingdom.
Differentiate the Evaluator, Not the Program: An Efficient Runtime Representation for Neuro-Symbolic Learning
Jul 3, 2026Lucas ShenemanAutomatic Differentiation Differentiable Programming
Institute for Interdisciplinary Data Sciences University of Idaho
Saturation-Aware Robust Trajectory Optimization for Reusable Launch Vehicles via Differentiable Physics
Jul 2, 2026Liwei Chen, Tong QinTrajectory Optimization Robust Control
Beijing Institute of Aeronautical Systems Engineering, Beijing 100076, China
Decision-focused Sparse Tangent Portfolio Optimization
Jul 1, 2026Haeun Jeon, Seunghoon Choi, Hyunglip Bae +2Decision-Focused Learning Portfolio Optimization
Department of Industrial and Systems Engineering, Korea Advanced Institute of Science and Technology, Daejeon, Republic of Korea · Department of Big Data Convergence, and Bigdata Research Lab, Chonnam National University, Gwangju, Republic of Korea · Department of Industrial Engineering, Ulsan National Institute of Science and Technology, Ulsan, Republic of Korea
Elastic ODYN: Differentiable Optimization for Infeasible Control and Learning in Robotics
Jun 15, 2026Aristotelis Papatheodorou, Jose Rojas, Ioannis Havoutis +1Robotic Control Primal-Dual Optimization
Department of Engineering Science, University of Oxford, Oxford, UK · Robot Motor Intelligence (RoMI) Lab, Heriot-Watt University, Edinburgh, UK
Differentiable Packing of Irregular 3D Objects with Adaptive Container Estimation
Jun 15, 2026Palak Gupta, Shanmuganathan Raman3D Spatial Reasoning Differentiable Optimization
Indian Institute of Technology Gandhinagar, India
Scalable Deep Unfolding of Conic Optimizers
Jun 11, 2026Alex Oshin, Rahul Vodeb Ghosh, Evangelos A. TheodorouSemidefinite Programming Algorithm Unrolling
Georgia Institute of Technology
Compile Once, Differentiate Everywhere: A Differentiable Meta-Circular Interpreter
Jun 7, 2026Lucas ShenemanAutomatic Differentiation Program Synthesis
Institute for Interdisciplinary Data Sciences University of Idaho
Beyond the Thin-Layer Limit: Differentiable Volumetric Training for Visible-Range Diffractive Neural Networks
Jun 5, 2026Dineth Jayakody, Dushan N. WadduwageDifferentiable Physics Differentiable Optimization
Department of Computer Science, Old Dominion University, Norfolk, VA 23529, USA · School of Data Science, Old Dominion University, Norfolk, VA 23529, USA · Department of Physics, Old Dominion University, Norfolk, VA 23529, USA
DIFFRACT: Neuralized Utility Maximization for Wireless Networks by Differentiable Programming
Jun 5, 2026Chee Wei Tan, Siya ChenAlgorithm Unrolling Wireless Resource Allocation
Nanyang Technological University, Singapore, Nanyang Ave., Singapore · Department of Computer Science, City University of Hong Kong, Hong Kong
DiffSlack: Learning under Nonlinear Inequality Constraints via Learnable Slack Variables
Jun 3, 2026Ziqian Wang, Chenxi Fang, Zhen ZhangConstrained Optimization Differentiable Optimization
State Key Laboratory of Tribology in Advanced Equipment, Tsinghua University, Beijing 100084, China · Beijing Key Laboratory of Transformative High-end Manufacturing Equipment and Technology, Department of Mechanical Engineering, Tsinghua University, Beijing 100084, China · Automotive Electronics Business Unit at Hirain Inc., China
Regularized Large Neighborhood Search
Jun 1, 2026Germain Vivier-Ardisson, Laurent Demonet, Axel Parmentier +1Markov Chain Monte Carlo Metaheuristic Optimization
Google DeepMind & CERMICS · Google Research · CERMICS, ENPC, CNRS, IPP +1

Oct 6, 2026, cs.LGJ/K move · Enter open · S save

Decision-Focused Learning in MDPs: An Occupancy Measure Approach

Zihao Zhao, Ashwath K. Karunakaram, Ali Eshragh, Yuexing Li+1

Georgia Institute of Technology, Atlanta, GA · Johns Hopkins Carey Business School, Washington, DC · International Computer Science Institute, Berkeley, CA

Markov Decision Processes Decision-Focused Learning Differentiable Optimization

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In this work, we consider decision-focused learning (DFL) for a Markov decision process (MDP), where existing methods differentiate through the KKT conditions of the Bellman equation and require solving a linear system over all state-action pairs, limiting its scalability. We address this by reformulating the MDP as an occupancy measure-based linear program (LP), whose feasible region is induced by predicted dynamics, and we derive a closed-form gradient by identifying the active constraints in the feasible polyhedron via the pivoting algorithm. This occupancy measure-based LP layer raises two challenges: (1) LP's solution gradient is discontinuous when active constraints change, and (2) the LP backward cost still scales with the state size, which is costly for large or continuous state spaces. We address the challenges with an augmented Lagrangian surrogate and smooth the boundary jumps by random row sketching of the constraints, and a learnable soft state-aggregation layer and its function-approximation generalization that scales the LP to large finite and continuous-state MDPs. Across multiple tasks, our methods reach lower regret than KKT-based DFL and two-stage baselines with significantly lower computation cost. The source code for all experiments is available at https://github.com/A-Eshragh/State_Aggregation_Project.

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