Guardado en:
| Autor principal: | Manoj, Naren Sarayu |
|---|---|
| Formato: | Preprint |
| Publicado: |
2025
|
| Materias: | |
| Acceso en línea: | https://arxiv.org/abs/2504.16270 |
| Etiquetas: |
Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
|
Ejemplares similares
Robust Least-Squares Optimization for Data-Driven Predictive Control: A Geometric Approach
por: Bharadwaj, Shreyas, et al.
Publicado: (2025)
por: Bharadwaj, Shreyas, et al.
Publicado: (2025)
A Graph-Partitioning Based Continuous Optimization Approach to Semi-supervised Clustering Problems
por: Liu, Wei, et al.
Publicado: (2025)
por: Liu, Wei, et al.
Publicado: (2025)
A Fenchel-Young Loss Approach to Data-Driven Inverse Optimization
por: Li, Zhehao, et al.
Publicado: (2025)
por: Li, Zhehao, et al.
Publicado: (2025)
A Mathematical Optimization Approach to Multisphere Support Vector Data Description
por: Blanco, Víctor, et al.
Publicado: (2025)
por: Blanco, Víctor, et al.
Publicado: (2025)
A Novel Hybrid Heuristic-Reinforcement Learning Optimization Approach for a Class of Railcar Shunting Problems
por: Zhao, Ruonan, et al.
Publicado: (2026)
por: Zhao, Ruonan, et al.
Publicado: (2026)
Inverse Optimization for Routing Problems
por: Scroccaro, Pedro Zattoni, et al.
Publicado: (2023)
por: Scroccaro, Pedro Zattoni, et al.
Publicado: (2023)
Bayesian Optimization of Bilevel Problems
por: Ekmekcioglu, Omer, et al.
Publicado: (2024)
por: Ekmekcioglu, Omer, et al.
Publicado: (2024)
Assessing and Enhancing Graph Neural Networks for Combinatorial Optimization: Novel Approaches and Application in Maximum Independent Set Problems
por: Hu, Chenchuhui
Publicado: (2024)
por: Hu, Chenchuhui
Publicado: (2024)
Bayesian Optimization for Non-Convex Two-Stage Stochastic Optimization Problems
por: Buckingham, Jack M., et al.
Publicado: (2024)
por: Buckingham, Jack M., et al.
Publicado: (2024)
Problem-Parameter-Free Decentralized Bilevel Optimization
por: Zhai, Zhiwei, et al.
Publicado: (2025)
por: Zhai, Zhiwei, et al.
Publicado: (2025)
Diffusion Stochastic Optimization for Min-Max Problems
por: Cai, Haoyuan, et al.
Publicado: (2024)
por: Cai, Haoyuan, et al.
Publicado: (2024)
Learning Surrogate Potential Mean Field Games via Gaussian Processes: A Data-Driven Approach to Ill-Posed Inverse Problems
por: Zhang, Jingguo, et al.
Publicado: (2025)
por: Zhang, Jingguo, et al.
Publicado: (2025)
The Data-Driven Censored Newsvendor Problem
por: Hssaine, Chamsi, et al.
Publicado: (2024)
por: Hssaine, Chamsi, et al.
Publicado: (2024)
A Support-Set Algorithm for Optimization Problems with Nonnegative and Orthogonal Constraints
por: Wang, Lei, et al.
Publicado: (2025)
por: Wang, Lei, et al.
Publicado: (2025)
humancompatible.train: Implementing Optimization Algorithms for Stochastically-Constrained Stochastic Optimization Problems
por: Kliachkin, Andrii, et al.
Publicado: (2025)
por: Kliachkin, Andrii, et al.
Publicado: (2025)
Global Optimization: A Machine Learning Approach
por: Bertsimas, Dimitris, et al.
Publicado: (2023)
por: Bertsimas, Dimitris, et al.
Publicado: (2023)
Block Decomposable Methods for Large-Scale Optimization Problems
por: Maia, Leandro Farias
Publicado: (2026)
por: Maia, Leandro Farias
Publicado: (2026)
You Shall Pass: Dealing with the Zero-Gradient Problem in Predict and Optimize for Convex Optimization
por: Veviurko, Grigorii, et al.
Publicado: (2023)
por: Veviurko, Grigorii, et al.
Publicado: (2023)
Machine Learning for Inverse Problems and Data Assimilation
por: Bach, Eviatar, et al.
Publicado: (2024)
por: Bach, Eviatar, et al.
Publicado: (2024)
A Split-Client Approach to Second-Order Optimization
por: Chayti, El Mahdi, et al.
Publicado: (2025)
por: Chayti, El Mahdi, et al.
Publicado: (2025)
Stochastic Constrained Decentralized Optimization for Machine Learning with Fewer Data Oracles: a Gradient Sliding Approach
por: Nguyen, Hoang Huy, et al.
Publicado: (2024)
por: Nguyen, Hoang Huy, et al.
Publicado: (2024)
Deep Reinforcement Learning: A Convex Optimization Approach
por: Gattami, Ather
Publicado: (2024)
por: Gattami, Ather
Publicado: (2024)
A Retrospective Approximation Approach for Smooth Stochastic Optimization
por: Newton, David, et al.
Publicado: (2021)
por: Newton, David, et al.
Publicado: (2021)
A Homogenization Approach for Gradient-Dominated Stochastic Optimization
por: Tan, Jiyuan, et al.
Publicado: (2023)
por: Tan, Jiyuan, et al.
Publicado: (2023)
Learning to Solve Optimization Problems Constrained with Partial Differential Equations
por: Guven, Yusuf, et al.
Publicado: (2025)
por: Guven, Yusuf, et al.
Publicado: (2025)
Optimality-Informed Neural Networks for Solving Parametric Optimization Problems
por: Hoffmann, Matthias K., et al.
Publicado: (2025)
por: Hoffmann, Matthias K., et al.
Publicado: (2025)
Simultaneous Learning and Optimization via Misspecified Saddle Point Problems
por: Ahmadi, Mohammad Mahdi, et al.
Publicado: (2025)
por: Ahmadi, Mohammad Mahdi, et al.
Publicado: (2025)
Surrogate-based Optimization via Clustering for Box-Constrained Problems
por: Ahmad, Maaz, et al.
Publicado: (2026)
por: Ahmad, Maaz, et al.
Publicado: (2026)
Stability of Data-Dependent Ridge-Regularization for Inverse Problems
por: Neumayer, Sebastian, et al.
Publicado: (2024)
por: Neumayer, Sebastian, et al.
Publicado: (2024)
Reinforcement Learning Approaches for the Orienteering Problem with Stochastic and Dynamic Release Dates
por: Li, Yuanyuan, et al.
Publicado: (2022)
por: Li, Yuanyuan, et al.
Publicado: (2022)
Stein Boltzmann Sampling: A Variational Approach for Global Optimization
por: Serré, Gaëtan, et al.
Publicado: (2024)
por: Serré, Gaëtan, et al.
Publicado: (2024)
Adaptivity and Universality: Problem-dependent Universal Regret for Online Convex Optimization
por: Zhao, Peng, et al.
Publicado: (2025)
por: Zhao, Peng, et al.
Publicado: (2025)
Collaborative Pareto Set Learning in Multiple Multi-Objective Optimization Problems
por: Shang, Chikai, et al.
Publicado: (2024)
por: Shang, Chikai, et al.
Publicado: (2024)
Learning of Linear Dynamical Systems as a Non-Commutative Polynomial Optimization Problem
por: Zhou, Quan, et al.
Publicado: (2020)
por: Zhou, Quan, et al.
Publicado: (2020)
Catastrophe Insurance: An Adaptive Robust Optimization Approach
por: Bertsimas, Dimitris, et al.
Publicado: (2024)
por: Bertsimas, Dimitris, et al.
Publicado: (2024)
A Bilevel Optimization Framework for Imbalanced Data Classification
por: Medlin, Karen, et al.
Publicado: (2024)
por: Medlin, Karen, et al.
Publicado: (2024)
Matrix Completion with Graph Information: A Provable Nonconvex Optimization Approach
por: Wang, Yao, et al.
Publicado: (2025)
por: Wang, Yao, et al.
Publicado: (2025)
A Machine Learning Approach to Two-Stage Adaptive Robust Optimization
por: Bertsimas, Dimitris, et al.
Publicado: (2023)
por: Bertsimas, Dimitris, et al.
Publicado: (2023)
Active Learning For Contextual Linear Optimization: A Margin-Based Approach
por: Liu, Mo, et al.
Publicado: (2023)
por: Liu, Mo, et al.
Publicado: (2023)
Low-Rank Extragradient Method for Nonsmooth and Low-Rank Matrix Optimization Problems
por: Garber, Dan, et al.
Publicado: (2022)
por: Garber, Dan, et al.
Publicado: (2022)
Ejemplares similares
-
Robust Least-Squares Optimization for Data-Driven Predictive Control: A Geometric Approach
por: Bharadwaj, Shreyas, et al.
Publicado: (2025) -
A Graph-Partitioning Based Continuous Optimization Approach to Semi-supervised Clustering Problems
por: Liu, Wei, et al.
Publicado: (2025) -
A Fenchel-Young Loss Approach to Data-Driven Inverse Optimization
por: Li, Zhehao, et al.
Publicado: (2025) -
A Mathematical Optimization Approach to Multisphere Support Vector Data Description
por: Blanco, Víctor, et al.
Publicado: (2025) -
A Novel Hybrid Heuristic-Reinforcement Learning Optimization Approach for a Class of Railcar Shunting Problems
por: Zhao, Ruonan, et al.
Publicado: (2026)