Parameter-free Mirror Descent
Fuente:
arXiv
Guardado en:
| Autores principales: | Jacobsen, Andrew, Cutkosky, Ashok |
|---|---|
| Formato: | Preprint |
| Publicado: |
2022
|
| Materias: | |
| Acceso en línea: | |
| Etiquetas: |
Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
|
Ejemplares similares
General framework for online-to-nonconvex conversion: Schedule-free SGD is also effective for nonconvex optimization
por: Ahn, Kwangjun, et al.
Publicado: (2024)
por: Ahn, Kwangjun, et al.
Publicado: (2024)
Adam with model exponential moving average is effective for nonconvex optimization
por: Ahn, Kwangjun, et al.
Publicado: (2024)
por: Ahn, Kwangjun, et al.
Publicado: (2024)
Unconstrained Robust Online Convex Optimization
por: Zhang, Jiujia, et al.
Publicado: (2025)
por: Zhang, Jiujia, et al.
Publicado: (2025)
Random Scaling and Momentum for Non-smooth Non-convex Optimization
por: Zhang, Qinzi, et al.
Publicado: (2024)
por: Zhang, Qinzi, et al.
Publicado: (2024)
Fully Unconstrained Online Learning
por: Cutkosky, Ashok, et al.
Publicado: (2024)
por: Cutkosky, Ashok, et al.
Publicado: (2024)
Optimal Stochastic Non-smooth Non-convex Optimization through Online-to-Non-convex Conversion
por: Cutkosky, Ashok, et al.
Publicado: (2023)
por: Cutkosky, Ashok, et al.
Publicado: (2023)
Reevaluating Theoretical Analysis Methods for Optimization in Deep Learning
por: Tran, Hoang, et al.
Publicado: (2024)
por: Tran, Hoang, et al.
Publicado: (2024)
Mirror Descent on Riemannian Manifolds
por: Jiang, Jiaxin, et al.
Publicado: (2026)
por: Jiang, Jiaxin, et al.
Publicado: (2026)
A Mirror Descent Perspective of Smoothed Sign Descent
por: Wang, Shuyang, et al.
Publicado: (2024)
por: Wang, Shuyang, et al.
Publicado: (2024)
Parameter-free Clipped Gradient Descent Meets Polyak
por: Takezawa, Yuki, et al.
Publicado: (2024)
por: Takezawa, Yuki, et al.
Publicado: (2024)
Private Zeroth-Order Nonsmooth Nonconvex Optimization
por: Zhang, Qinzi, et al.
Publicado: (2024)
por: Zhang, Qinzi, et al.
Publicado: (2024)
On the Convergence of Policy in Unregularized Policy Mirror Descent
por: Lin, Dachao, et al.
Publicado: (2022)
por: Lin, Dachao, et al.
Publicado: (2022)
Mirror Descent on Reproducing Kernel Banach Spaces
por: Kumar, Akash, et al.
Publicado: (2024)
por: Kumar, Akash, et al.
Publicado: (2024)
Mirror and Preconditioned Gradient Descent in Wasserstein Space
por: Bonet, Clément, et al.
Publicado: (2024)
por: Bonet, Clément, et al.
Publicado: (2024)
Value Mirror Descent for Reinforcement Learning
por: Jia, Zhichao, et al.
Publicado: (2026)
por: Jia, Zhichao, et al.
Publicado: (2026)
Implicit Bias and Convergence of Matrix Stochastic Mirror Descent
por: Akhtiamov, Danil, et al.
Publicado: (2026)
por: Akhtiamov, Danil, et al.
Publicado: (2026)
On the Convergence of Policy Mirror Descent with Temporal Difference Evaluation
por: Liu, Jiacai, et al.
Publicado: (2025)
por: Liu, Jiacai, et al.
Publicado: (2025)
Convergence of Policy Mirror Descent Beyond Compatible Function Approximation
por: Sherman, Uri, et al.
Publicado: (2025)
por: Sherman, Uri, et al.
Publicado: (2025)
Mirror Descent-Type Algorithms for the Variational Inequality Problem with Functional Constraints
por: Alkousa, Mohammad S., et al.
Publicado: (2026)
por: Alkousa, Mohammad S., et al.
Publicado: (2026)
Zeroth-Order Stochastic Mirror Descent Algorithms for Minimax Excess Risk Optimization
por: Gu, Zhihao, et al.
Publicado: (2024)
por: Gu, Zhihao, et al.
Publicado: (2024)
Mirror Descent-Ascent for mean-field min-max problems
por: Lascu, Razvan-Andrei, et al.
Publicado: (2024)
por: Lascu, Razvan-Andrei, et al.
Publicado: (2024)
Policy Mirror Descent with Temporal Difference Learning: Sample Complexity under Online Markov Data
por: Li, Wenye, et al.
Publicado: (2025)
por: Li, Wenye, et al.
Publicado: (2025)
An Equivalence Between Static and Dynamic Regret Minimization
por: Jacobsen, Andrew, et al.
Publicado: (2024)
por: Jacobsen, Andrew, et al.
Publicado: (2024)
Parameter Symmetry and Noise Equilibrium of Stochastic Gradient Descent
por: Ziyin, Liu, et al.
Publicado: (2024)
por: Ziyin, Liu, et al.
Publicado: (2024)
A connection between Tempering and Entropic Mirror Descent
por: Chopin, Nicolas, et al.
Publicado: (2023)
por: Chopin, Nicolas, et al.
Publicado: (2023)
DoWG Unleashed: An Efficient Universal Parameter-Free Gradient Descent Method
por: Khaled, Ahmed, et al.
Publicado: (2023)
por: Khaled, Ahmed, et al.
Publicado: (2023)
The Road Less Scheduled
por: Defazio, Aaron, et al.
Publicado: (2024)
por: Defazio, Aaron, et al.
Publicado: (2024)
A Novel Framework for Policy Mirror Descent with General Parameterization and Linear Convergence
por: Alfano, Carlo, et al.
Publicado: (2023)
por: Alfano, Carlo, et al.
Publicado: (2023)
Stochastic Adaptive Gradient Descent Without Descent
por: Aujol, Jean-François, et al.
Publicado: (2025)
por: Aujol, Jean-François, et al.
Publicado: (2025)
Asynchronous Distributed Optimization with Delay-free Parameters
por: Wu, Xuyang, et al.
Publicado: (2023)
por: Wu, Xuyang, et al.
Publicado: (2023)
Parameter-free Algorithms for the Stochastically Extended Adversarial Model
por: Wang, Shuche, et al.
Publicado: (2025)
por: Wang, Shuche, et al.
Publicado: (2025)
Mirror Descent Algorithms with Nearly Dimension-Independent Rates for Differentially-Private Stochastic Saddle-Point Problems
por: González, Tomás, et al.
Publicado: (2024)
por: González, Tomás, et al.
Publicado: (2024)
Quantitative Convergence Analysis of Projected Stochastic Gradient Descent for Non-Convex Losses via the Goldstein Subdifferential
por: Zheng, Yuping, et al.
Publicado: (2025)
por: Zheng, Yuping, et al.
Publicado: (2025)
The Method of Infinite Descent
por: Batley, Reza T., et al.
Publicado: (2025)
por: Batley, Reza T., et al.
Publicado: (2025)
Corner Gradient Descent
por: Yarotsky, Dmitry
Publicado: (2025)
por: Yarotsky, Dmitry
Publicado: (2025)
Random Function Descent
por: Benning, Felix, et al.
Publicado: (2023)
por: Benning, Felix, et al.
Publicado: (2023)
Online Linear Regression in Dynamic Environments via Discounting
por: Jacobsen, Andrew, et al.
Publicado: (2024)
por: Jacobsen, Andrew, et al.
Publicado: (2024)
Mirror Mean-Field Langevin Dynamics
por: Gu, Anming, et al.
Publicado: (2025)
por: Gu, Anming, et al.
Publicado: (2025)
A Local Polyak-Lojasiewicz and Descent Lemma of Gradient Descent For Overparametrized Linear Models
por: Xu, Ziqing, et al.
Publicado: (2025)
por: Xu, Ziqing, et al.
Publicado: (2025)
Adaptive Conditional Gradient Descent
por: Khademi, Abbas, et al.
Publicado: (2025)
por: Khademi, Abbas, et al.
Publicado: (2025)
Ejemplares similares
-
General framework for online-to-nonconvex conversion: Schedule-free SGD is also effective for nonconvex optimization
por: Ahn, Kwangjun, et al.
Publicado: (2024) -
Adam with model exponential moving average is effective for nonconvex optimization
por: Ahn, Kwangjun, et al.
Publicado: (2024) -
Unconstrained Robust Online Convex Optimization
por: Zhang, Jiujia, et al.
Publicado: (2025) -
Random Scaling and Momentum for Non-smooth Non-convex Optimization
por: Zhang, Qinzi, et al.
Publicado: (2024) -
Fully Unconstrained Online Learning
por: Cutkosky, Ashok, et al.
Publicado: (2024)