Imagen de Portada

Multiple Wasserstein Gradient Descent Algorithm for Multi-Objective Distributional Optimization

Fuente: arXiv

Guardado en:

Detalles Bibliográficos
Autores principales:	Nguyen, Dai Hai, Mamitsuka, Hiroshi, Nakamura, Atsuyoshi
Formato:	Preprint
Publicado:	2025
Materias:	Machine Learning
Acceso en línea:	Acceder al recurso
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

Ejemplares similares

Accelerated Multiple Wasserstein Gradient Flows for Multi-objective Distributional Optimization
por: Nguyen, Dai Hai, et al.
Publicado: (2026)

Wasserstein Gradient Flow over Variational Parameter Space for Variational Inference
por: Nguyen, Dai Hai, et al.
Publicado: (2023)

An Efficient Algorithm for Thresholding Monte Carlo Tree Search
por: Nameki, Shoma, et al.
Publicado: (2026)

Multi-Objective Optimization via Wasserstein-Fisher-Rao Gradient Flow
por: Ren, Yinuo, et al.
Publicado: (2023)

PSMGD: Periodic Stochastic Multi-Gradient Descent for Fast Multi-Objective Optimization
por: Xu, Mingjing, et al.
Publicado: (2024)

PMGDA: A Preference-based Multiple Gradient Descent Algorithm
por: Zhang, Xiaoyuan, et al.
Publicado: (2024)

Mirror and Preconditioned Gradient Descent in Wasserstein Space
por: Bonet, Clément, et al.
Publicado: (2024)

Jacobian Descent for Multi-Objective Optimization
por: Quinton, Pierre, et al.
Publicado: (2024)

A First-Order Multi-Gradient Algorithm for Multi-Objective Bi-Level Optimization
por: Ye, Feiyang, et al.
Publicado: (2024)

Fast Estimation of Wasserstein Distances via Regression on Sliced Wasserstein Distances
por: Nguyen, Khai, et al.
Publicado: (2025)

Long-term Detection System for Six Kinds of Abnormal Behavior of the Elderly Living Alone
por: Tanaka, Kai, et al.
Publicado: (2024)

Moreau-Yoshida Variational Transport: A General Framework For Solving Regularized Distributional Optimization Problems
por: Nguyen, Dai Hai, et al.
Publicado: (2023)

A Mirror Descent-Based Algorithm for Corruption-Tolerant Distributed Gradient Descent
por: Wang, Shuche, et al.
Publicado: (2024)

Exploring the Optimized Value of Each Hyperparameter in Various Gradient Descent Algorithms
por: Chen, Abel C. H.
Publicado: (2022)

Gradient Descent Algorithm Survey
por: Fucheng, Deng, et al.
Publicado: (2025)

Distributed Gradient Descent for Functional Learning
por: Yu, Zhan, et al.
Publicado: (2023)

Accelerating Feedback-based Algorithms for Quantum Optimization Using Gradient Descent
por: Mozakka, Masih, et al.
Publicado: (2026)

Two-Timescale Gradient Descent Ascent Algorithms for Nonconvex Minimax Optimization
por: Lin, Tianyi, et al.
Publicado: (2024)

Towards Marginal Fairness Sliced Wasserstein Barycenter
por: Nguyen, Khai, et al.
Publicado: (2024)

Joint Optimization of Multi-Objective Reinforcement Learning with Policy Gradient Based Algorithm
por: Bai, Qinbo, et al.
Publicado: (2021)

Stochastic Re-weighted Gradient Descent via Distributionally Robust Optimization
por: Kumar, Ramnath, et al.
Publicado: (2023)

Geodesic Gradient Descent: A Generic and Learning-rate-free Optimizer on Objective Function-induced Manifolds
por: Hu, Liwei, et al.
Publicado: (2026)

Multi-Objective Reward and Preference Optimization: Theory and Algorithms
por: Agnihotri, Akhil
Publicado: (2025)

Multi-objective Portfolio Optimization Via Gradient Descent
por: Oliva, Christian, et al.
Publicado: (2025)

Distributionally Robust Multi-Objective Optimization
por: Yang, Yufeng, et al.
Publicado: (2026)

Stochastic Gradient Descent with Momentum is Algorithmically Stable
por: Lei, Yunwen, et al.
Publicado: (2026)

Gradient-Based Multi-Objective Deep Learning: Algorithms, Theories, Applications, and Beyond
por: Chen, Weiyu, et al.
Publicado: (2025)

Wasserstein Distributionally Robust Optimization: Theory and Applications in Machine Learning
por: Kuhn, Daniel, et al.
Publicado: (2019)

Knowledge Gradient for Multi-Objective Bayesian Optimization with Decoupled Evaluations
por: Buckingham, Jack M., et al.
Publicado: (2023)

Quantum Shadow Gradient Descent for Variational Quantum Algorithms
por: Heidari, Mohsen, et al.
Publicado: (2023)

The Power of Random Features and the Limits of Distribution-Free Gradient Descent
por: Karchmer, Ari, et al.
Publicado: (2025)

Dynamic Decoupling of Placid Terminal Attractor-based Gradient Descent Algorithm
por: Zhao, Jinwei, et al.
Publicado: (2024)

Enhancing Fractional Gradient Descent with Learned Optimizers
por: Sobotka, Jan, et al.
Publicado: (2025)

Preconditioning for Accelerated Gradient Descent Optimization and Regularization
por: Ye, Qiang
Publicado: (2024)

Rapid Overfitting of Multi-Pass Stochastic Gradient Descent in Stochastic Convex Optimization
por: Vansover-Hager, Shira, et al.
Publicado: (2025)

Occam Gradient Descent
por: Kausik, B. N.
Publicado: (2024)

DDEQs: Distributional Deep Equilibrium Models through Wasserstein Gradient Flows
por: Geuter, Jonathan, et al.
Publicado: (2025)

Noise Balance and Stationary Distribution of Stochastic Gradient Descent
por: Ziyin, Liu, et al.
Publicado: (2023)

On the Optimization and Generalization of Two-layer Transformers with Sign Gradient Descent
por: Li, Bingrui, et al.
Publicado: (2024)

Quantum Algorithm for Sparse Online Learning with Truncated Gradient Descent
por: Lim, Debbie, et al.
Publicado: (2024)