Decision-Focused Federated Learning Under Heterogeneous Objectives and Constraints
Fuente:
arXiv
Guardado en:
| Autores principales: | Ziliaskopoulos, Konstantinos, Vinel, Alexander |
|---|---|
| Formato: | Preprint |
| Publicado: |
2026
|
| Materias: | |
| Acceso en línea: | |
| Etiquetas: |
Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
|
Ejemplares similares
Sufficient Decision Proxies for Decision-Focused Learning
por: Schutte, Noah, et al.
Publicado: (2025)
por: Schutte, Noah, et al.
Publicado: (2025)
Robust Losses for Decision-Focused Learning
por: Schutte, Noah, et al.
Publicado: (2023)
por: Schutte, Noah, et al.
Publicado: (2023)
Decision-Focused Learning with Directional Gradients
por: Huang, Michael, et al.
Publicado: (2024)
por: Huang, Michael, et al.
Publicado: (2024)
Private Networked Federated Learning for Nonsmooth Objectives
por: Gauthier, François, et al.
Publicado: (2023)
por: Gauthier, François, et al.
Publicado: (2023)
On the Robustness of Decision-Focused Learning
por: Farhat, Yehya
Publicado: (2023)
por: Farhat, Yehya
Publicado: (2023)
On Performance Guarantees for Federated Learning with Personalized Constraints
por: Ebrahimi, Mohammadjavad, et al.
Publicado: (2026)
por: Ebrahimi, Mohammadjavad, et al.
Publicado: (2026)
Subspace Optimization for Efficient Federated Learning under Heterogeneous Data
por: Zhu, Shuchen, et al.
Publicado: (2026)
por: Zhu, Shuchen, et al.
Publicado: (2026)
Communication Efficient Federated Learning with Linear Convergence on Heterogeneous Data
por: Liu, Jie, et al.
Publicado: (2025)
por: Liu, Jie, et al.
Publicado: (2025)
Finite-Time Analysis of On-Policy Heterogeneous Federated Reinforcement Learning
por: Zhang, Chenyu, et al.
Publicado: (2024)
por: Zhang, Chenyu, et al.
Publicado: (2024)
Constrained Stochastic Spectral Preconditioning Converges for Nonconvex Objectives
por: Oikonomidis, Konstantinos, et al.
Publicado: (2026)
por: Oikonomidis, Konstantinos, et al.
Publicado: (2026)
A Randomized Zeroth-Order Hierarchical Framework for Heterogeneous Federated Learning
por: Qiu, Yuyang, et al.
Publicado: (2025)
por: Qiu, Yuyang, et al.
Publicado: (2025)
SCAFFLSA: Taming Heterogeneity in Federated Linear Stochastic Approximation and TD Learning
por: Mangold, Paul, et al.
Publicado: (2024)
por: Mangold, Paul, et al.
Publicado: (2024)
Shadowheart SGD: Distributed Asynchronous SGD with Optimal Time Complexity Under Arbitrary Computation and Communication Heterogeneity
por: Tyurin, Alexander, et al.
Publicado: (2024)
por: Tyurin, Alexander, et al.
Publicado: (2024)
Muon Optimizes Under Spectral Norm Constraints
por: Chen, Lizhang, et al.
Publicado: (2025)
por: Chen, Lizhang, et al.
Publicado: (2025)
Compressed Proximal Federated Learning for Non-Convex Composite Optimization on Heterogeneous Data
por: Qiu, Pu, et al.
Publicado: (2026)
por: Qiu, Pu, et al.
Publicado: (2026)
Federated Temporal Difference Learning with Linear Function Approximation under Environmental Heterogeneity
por: Wang, Han, et al.
Publicado: (2023)
por: Wang, Han, et al.
Publicado: (2023)
Online Markov Decision Processes with Terminal Law Constraints
por: Moreno, Bianca Marin, et al.
Publicado: (2026)
por: Moreno, Bianca Marin, et al.
Publicado: (2026)
Accelerated Methods with Complexity Separation Under Data Similarity for Federated Learning Problems
por: Bylinkin, Dmitry, et al.
Publicado: (2026)
por: Bylinkin, Dmitry, et al.
Publicado: (2026)
Decision-Focused Learning: Foundations, State of the Art, Benchmark and Future Opportunities
por: Mandi, Jayanta, et al.
Publicado: (2023)
por: Mandi, Jayanta, et al.
Publicado: (2023)
QCQP-Net: Reliably Learning Feasible Alternating Current Optimal Power Flow Solutions Under Constraints
por: Zeng, Sihan, et al.
Publicado: (2024)
por: Zeng, Sihan, et al.
Publicado: (2024)
The Gittins Index: A Design Principle for Decision-Making Under Uncertainty
por: Scully, Ziv, et al.
Publicado: (2025)
por: Scully, Ziv, et al.
Publicado: (2025)
Towards The Implicit Bias on Multiclass Separable Data Under Norm Constraints
por: Xie, Shengping, et al.
Publicado: (2026)
por: Xie, Shengping, et al.
Publicado: (2026)
Decision-Focused Bias Correction for Fluid Approximation
por: Er, Can, et al.
Publicado: (2025)
por: Er, Can, et al.
Publicado: (2025)
Optimizing Inventory Routing: A Decision-Focused Learning Approach using Neural Networks
por: Islam, MD Shafikul, et al.
Publicado: (2023)
por: Islam, MD Shafikul, et al.
Publicado: (2023)
Exploring New Frontiers in Vertical Federated Learning: the Role of Saddle Point Reformulation
por: Beznosikov, Aleksandr, et al.
Publicado: (2026)
por: Beznosikov, Aleksandr, et al.
Publicado: (2026)
Locally Adaptive Multi-Objective Learning
por: Kaur, Jivat Neet, et al.
Publicado: (2026)
por: Kaur, Jivat Neet, et al.
Publicado: (2026)
FERERO: A Flexible Framework for Preference-Guided Multi-Objective Learning
por: Chen, Lisha, et al.
Publicado: (2024)
por: Chen, Lisha, et al.
Publicado: (2024)
Collaborative Pareto Set Learning in Multiple Multi-Objective Optimization Problems
por: Shang, Chikai, et al.
Publicado: (2024)
por: Shang, Chikai, et al.
Publicado: (2024)
Inverse Mixed-Integer Programming: Learning Constraints then Objective Functions
por: Kitaoka, Akira
Publicado: (2025)
por: Kitaoka, Akira
Publicado: (2025)
Momentum for the Win: Collaborative Federated Reinforcement Learning across Heterogeneous Environments
por: Wang, Han, et al.
Publicado: (2024)
por: Wang, Han, et al.
Publicado: (2024)
Learning to Cover: Online Learning and Optimization with Irreversible Decisions
por: Jacquillat, Alexandre, et al.
Publicado: (2024)
por: Jacquillat, Alexandre, et al.
Publicado: (2024)
The inexact power augmented Lagrangian method for constrained nonconvex optimization
por: Bodard, Alexander, et al.
Publicado: (2024)
por: Bodard, Alexander, et al.
Publicado: (2024)
Multi-Objective Optimization-Based Anonymization of Structured Data for Machine Learning Application
por: Wei, Yusi, et al.
Publicado: (2025)
por: Wei, Yusi, et al.
Publicado: (2025)
Enhancing Multi-Objective Optimization through Machine Learning-Supported Multiphysics Simulation
por: Botache, Diego, et al.
Publicado: (2023)
por: Botache, Diego, et al.
Publicado: (2023)
Pareto Front Shape-Agnostic Pareto Set Learning in Multi-Objective Optimization
por: Ye, Rongguang, et al.
Publicado: (2024)
por: Ye, Rongguang, et al.
Publicado: (2024)
Traversing Pareto Optimal Policies: Provably Efficient Multi-Objective Reinforcement Learning
por: Qiu, Shuang, et al.
Publicado: (2024)
por: Qiu, Shuang, et al.
Publicado: (2024)
FedSGM: A Unified Framework for Constraint Aware, Bidirectionally Compressed, Multi-Step Federated Optimization
por: Upadhyay, Antesh, et al.
Publicado: (2026)
por: Upadhyay, Antesh, et al.
Publicado: (2026)
Aligned Multi Objective Optimization
por: Efroni, Yonathan, et al.
Publicado: (2025)
por: Efroni, Yonathan, et al.
Publicado: (2025)
Structured Reinforcement Learning for Combinatorial Decision-Making
por: Hoppe, Heiko, et al.
Publicado: (2025)
por: Hoppe, Heiko, et al.
Publicado: (2025)
Locally Adaptive Federated Learning
por: Mukherjee, Sohom, et al.
Publicado: (2023)
por: Mukherjee, Sohom, et al.
Publicado: (2023)
Ejemplares similares
-
Sufficient Decision Proxies for Decision-Focused Learning
por: Schutte, Noah, et al.
Publicado: (2025) -
Robust Losses for Decision-Focused Learning
por: Schutte, Noah, et al.
Publicado: (2023) -
Decision-Focused Learning with Directional Gradients
por: Huang, Michael, et al.
Publicado: (2024) -
Private Networked Federated Learning for Nonsmooth Objectives
por: Gauthier, François, et al.
Publicado: (2023) -
On the Robustness of Decision-Focused Learning
por: Farhat, Yehya
Publicado: (2023)