Cover Image

Enforcing Hard Linear Constraints in Deep Learning Models with Decision Rules

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Constante-Flores, Gonzalo E., Chen, Hao, Li, Can
Format:	Preprint
Published:	2025
Subjects:	Machine Learning
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Physics-Informed Neural Networks with Hard Linear Equality Constraints
by: Chen, Hao, et al.
Published: (2024)

FaultExplainer: Leveraging Large Language Models for Interpretable Fault Detection and Diagnosis
by: Khan, Abdullah, et al.
Published: (2024)

Deep Generative Models with Hard Linear Equality Constraints
by: Li, Ruoyan, et al.
Published: (2025)

DAE-HardNet: A Physics Constrained Neural Network Enforcing Differential-Algebraic Hard Constraints
by: Golder, Rahul, et al.
Published: (2025)

Conformalized Prediction of Post-Fault Voltage Trajectories Using Pre-trained and Finetuned Attention-Driven Neural Operators
by: Mollaali, Amirhossein, et al.
Published: (2024)

OptiChat: Bridging Optimization Models and Practitioners with Large Language Models
by: Chen, Hao, et al.
Published: (2025)

Enforcing Constraints in Generative Sampling via Adaptive Correction Scheduling
by: Trupin, Noah, et al.
Published: (2026)

A Frobenius-Optimal Projection for Enforcing Linear Conservation in Learned Dynamical Models
by: Mango, John M., et al.
Published: (2025)

Learning Adversarial MDPs with Stochastic Hard Constraints
by: Stradi, Francesco Emanuele, et al.
Published: (2024)

Enforcing Fair Predicted Scores on Intervals of Percentiles by Difference-of-Convex Constraints
by: He, Yutian, et al.
Published: (2025)

Enforcing Reciprocity in Operator Learning for Seismic Wave Propagation
by: Zou, Caifeng, et al.
Published: (2026)

A Quadratically-Constrained Convex Approximation for the AC Optimal Power Flow
by: Constante-Flores, Gonzalo E., et al.
Published: (2025)

Learning Optimal Individualized Decision Rules with Conditional Demographic Parity
by: Cui, Wenhai, et al.
Published: (2026)

The Effect of Enforcing Fairness on Reshaping Explanations in Machine Learning Models
by: Anderson, Joshua Wolff, et al.
Published: (2025)

Understanding Learning Invariance in Deep Linear Networks
by: Duan, Hao, et al.
Published: (2025)

Predict-Project-Renoise: Sampling Diffusion Models under Hard Constraints
by: Rochman-Sharabi, Omer, et al.
Published: (2026)

DIM: Enforcing Domain-Informed Monotonicity in Deep Neural Networks
by: Salim, Joshua, et al.
Published: (2025)

ABS: Enforcing Constraint Satisfaction On Generated Sequences Via Automata-Guided Beam Search
by: Collura, Vincenzo, et al.
Published: (2025)

SB-TRPO: Towards Safe Reinforcement Learning with Hard Constraints
by: Wagner, Dominik, et al.
Published: (2025)

Joint Continual Learning of Local Language Models and Cloud Offloading Decisions with Budget Constraints
by: Chen, Evan, et al.
Published: (2026)

Dynamic Interpretability for Model Comparison via Decision Rules
by: Rida, Adam, et al.
Published: (2023)

A Quadratic Synchronization Rule for Distributed Deep Learning
by: Gu, Xinran, et al.
Published: (2023)

Privacy-Preserving Data Sharing in Agriculture: Enforcing Policy Rules for Secure and Confidential Data Synthesis
by: Kotal, Anantaa, et al.
Published: (2023)

Locally Interpretable Individualized Treatment Rules for Black-Box Decision Models
by: Charvadeh, Yasin Khadem, et al.
Published: (2026)

Sample-Efficient Policy Constraint Offline Deep Reinforcement Learning based on Sample Filtering
by: Chen, Yuanhao, et al.
Published: (2025)

HardNet++: Nonlinear Constraint Enforcement in Neural Networks
by: Goertzen, Andrea, et al.
Published: (2026)

CDR-Agent: Intelligent Selection and Execution of Clinical Decision Rules Using Large Language Model Agents
by: Xiang, Zhen, et al.
Published: (2025)

Learning the Inverse Temperature of Ising Models under Hard Constraints using One Sample
by: Chauhan, Rohan, et al.
Published: (2025)

A Neural Network Framework for Discovering Closed-form Solutions to Quadratic Programs with Linear Constraints
by: Beylunioglu, Fuat Can, et al.
Published: (2025)

Research on Autonomous Driving Decision-making Strategies based Deep Reinforcement Learning
by: Wang, Zixiang, et al.
Published: (2024)

Training Transformers with Enforced Lipschitz Constants
by: Newhouse, Laker, et al.
Published: (2025)

AdaFair-MARL: Enforcing Adaptive Fairness Constraints in Multi-Agent Reinforcement Learning
by: Ekpo, Promise, et al.
Published: (2025)

Development of Deep Learning Optimizers: Approaches, Concepts, and Update Rules
by: Altınel, Doğay
Published: (2025)

CombOptNet: Fit the Right NP-Hard Problem by Learning Integer Programming Constraints
by: Paulus, Anselm, et al.
Published: (2021)

Fast and Interpretable Mixed-Integer Linear Program Solving by Learning Model Reduction
by: Li, Yixuan, et al.
Published: (2024)

Neural Proposals, Symbolic Guarantees: Neuro-Symbolic Graph Generation with Hard Constraints
by: Geng, Chuqin, et al.
Published: (2026)

Fairness Constraints in High-Dimensional Generalized Linear Models
by: Lin, Yixiao, et al.
Published: (2026)

Hard-Constrained Deep Learning for Climate Downscaling
by: Harder, Paula, et al.
Published: (2022)

RAYEN: Imposition of Hard Convex Constraints on Neural Networks
by: Tordesillas, Jesus, et al.
Published: (2023)

Enforcing hidden physics in physics-informed neural networks
by: Chen, Nanxi, et al.
Published: (2025)