Cover Image

On PI Controllers for Updating Lagrange Multipliers in Constrained Optimization

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Sohrabi, Motahareh, Ramirez, Juan, Zhang, Tianyue H., Lacoste-Julien, Simon, Gallego-Posada, Jose
Format:	Preprint
Published:	2024
Subjects:	Machine Learning Optimization and Control
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Dual Optimistic Ascent (PI Control) is the Augmented Lagrangian Method in Disguise
by: Ramirez, Juan, et al.
Published: (2025)

Position: Adopt Constraints Over Fixed Penalties in Deep Learning
by: Ramirez, Juan, et al.
Published: (2025)

Self-supervised Equality Embedded Deep Lagrange Dual for Approximate Constrained Optimization
by: Kim, Minsoo, et al.
Published: (2023)

Cooper: A Library for Constrained Optimization in Deep Learning
by: Gallego-Posada, Jose, et al.
Published: (2025)

Lagrange Multipliers and Duality with Applications to Constrained Support Vector Machine
by: Nam, Nguyen Mau, et al.
Published: (2025)

Projection-Free Functional Constrained Optimization for Risk Aversion and Sparsity Control
by: Cheng, Yi, et al.
Published: (2022)

Weight-Sharing Regularization
by: Shakerinava, Mehran, et al.
Published: (2023)

Partial Lagrange Multiplier Expressions and Disjunctive Decompositions for Bilevel Optimization
by: Nie, Jiawang, et al.
Published: (2023)

Convergence of Distributed Adaptive Optimization with Local Updates
by: Cheng, Ziheng, et al.
Published: (2024)

Fundamental Benefit of Alternating Updates in Minimax Optimization
by: Lee, Jaewook, et al.
Published: (2024)

Full Waveform Inversion and Lagrange Multipliers
by: Gholami, Ali
Published: (2023)

HUANet: Hard-Constrained Unrolled ADMM for Constrained Convex Optimization
by: Tran, Trinh, et al.
Published: (2026)

First-Order Methods for Linearly Constrained Bilevel Optimization
by: Kornowski, Guy, et al.
Published: (2024)

Understanding Adam Optimizer via Online Learning of Updates: Adam is FTRL in Disguise
by: Ahn, Kwangjun, et al.
Published: (2024)

Automatic Differentiation of Optimization Algorithms with Time-Varying Updates
by: Mehmood, Sheheryar, et al.
Published: (2024)

Progressively Sampled Equality-Constrained Optimization
by: Curtis, Frank E., et al.
Published: (2025)

Gaussian Approximation and Multiplier Bootstrap for Federated Linear Stochastic Approximation
by: Levin, Ilya, et al.
Published: (2026)

Predicting Accurate Lagrangian Multipliers for Mixed Integer Linear Programs
by: Demelas, Francesco, et al.
Published: (2023)

The Role of Target Update Frequencies in Q-Learning
by: Weissmann, Simon, et al.
Published: (2026)

Accelerating Multi-Block Constrained Optimization Through Learning to Optimize
by: Liang, Ling, et al.
Published: (2024)

Online Dynamic Submodular Optimization
by: Lesage-Landry, Antoine, et al.
Published: (2023)

Enhancing GNNs Performance on Combinatorial Optimization by Recurrent Feature Update
by: Pugacheva, Daria, et al.
Published: (2024)

Stochastic-Constrained Stochastic Optimization with Markovian Data
by: Kim, Yeongjong, et al.
Published: (2023)

Conformal Predictive Programming for Chance Constrained Optimization
by: Zhao, Yiqi, et al.
Published: (2024)

First-Order Sparse Convex Optimization: Better Rates with Sparse Updates
by: Garber, Dan
Published: (2025)

humancompatible.train: Implementing Optimization Algorithms for Stochastically-Constrained Stochastic Optimization Problems
by: Kliachkin, Andrii, et al.
Published: (2025)

Self-Supervised Learning of Iterative Solvers for Constrained Optimization
by: Lüken, Lukas, et al.
Published: (2024)

Learning Constrained Optimization with Deep Augmented Lagrangian Methods
by: Kotary, James, et al.
Published: (2024)

Constrained Online Convex Optimization with Polyak Feasibility Steps
by: Hutchinson, Spencer, et al.
Published: (2025)

Safe-EF: Error Feedback for Nonsmooth Constrained Optimization
by: Islamov, Rustem, et al.
Published: (2025)

PINNs in PDE Constrained Optimal Control Problems: Direct vs Indirect Methods
by: Zhang, Zhen, et al.
Published: (2026)

Projection-Free Variance Reduction Methods for Stochastic Constrained Multi-Level Compositional Optimization
by: Jiang, Wei, et al.
Published: (2024)

Machine Learning for K-adaptability in Two-stage Robust Optimization
by: Julien, Esther, et al.
Published: (2022)

Constrained Bi-Level Optimization: Proximal Lagrangian Value function Approach and Hessian-free Algorithm
by: Yao, Wei, et al.
Published: (2024)

A Trust-Region Algorithm for Noisy Equality Constrained Optimization
by: Sun, Shigeng, et al.
Published: (2024)

Learning to Solve Optimization Problems Constrained with Partial Differential Equations
by: Guven, Yusuf, et al.
Published: (2025)

Randomized Feasibility Methods for Constrained Optimization with Adaptive Step Sizes
by: Chakraborty, Abhishek, et al.
Published: (2026)

Self-Supervised Penalty-Based Learning for Robust Constrained Optimization
by: Benslimane, Wyame, et al.
Published: (2025)

FSNet: Feasibility-Seeking Neural Network for Constrained Optimization with Guarantees
by: Nguyen, Hoang T., et al.
Published: (2025)

Surrogate-based Optimization via Clustering for Box-Constrained Problems
by: Ahmad, Maaz, et al.
Published: (2026)