:: Library Catalog

Cover Image

Saved in:

Bibliographic Details
Main Author:	Nguyen, Quan
Format:	Preprint
Published:	2025
Subjects:	Machine Learning Optimization and Control
Online Access:	https://arxiv.org/abs/2510.03478
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

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

Adam Converges Without Any Modification On Update Rules
by: Zhang, Yushun, et al.
Published: (2026)

Provable Adaptivity of Adam under Non-uniform Smoothness
by: Wang, Bohan, et al.
Published: (2022)

HomeAdam: Adam and AdamW Algorithms Sometimes Go Home to Obtain Better Provable Generalization
by: Huang, Feihu, et al.
Published: (2026)

Adam-HNAG: A Convergent Reformulation of Adam with Accelerated Rate
by: Yu, Yaxin, et al.
Published: (2026)

Adam on Local Time: Addressing Nonstationarity in RL with Relative Adam Timesteps
by: Ellis, Benjamin, et al.
Published: (2024)

A Theoretical and Empirical Study on the Convergence of Adam with an "Exact" Constant Step Size in Non-Convex Settings
by: Mazumder, Alokendu, et al.
Published: (2023)

Projection-free Online Learning over Strongly Convex Sets
by: Wan, Yuanyu, et al.
Published: (2020)

Majorization-minimization for Sparse Nonnegative Matrix Factorization with the $β$-divergence
by: Marmin, Arthur, et al.
Published: (2022)

Adam-SHANG: A Convergent Adam-Type Method for Stochastic Smooth Convex Optimization
by: Yu, Yaxin, et al.
Published: (2026)

The Sample Complexity of Online Reinforcement Learning: A Multi-model Perspective
by: Muehlebach, Michael, et al.
Published: (2025)

Level Set Teleportation: An Optimization Perspective
by: Mishkin, Aaron, et al.
Published: (2024)

Online Inventory Problems: Beyond the i.i.d. Setting with Online Convex Optimization
by: Hihat, Massil, et al.
Published: (2023)

Efficient First-Order Optimization on the Pareto Set for Multi-Objective Learning under Preference Guidance
by: Chen, Lisha, et al.
Published: (2025)

The Rich and the Simple: On the Implicit Bias of Adam and SGD
by: Vasudeva, Bhavya, et al.
Published: (2025)

Convergence rates for the Adam optimizer
by: Dereich, Steffen, et al.
Published: (2024)

Adam-family Methods for Nonsmooth Optimization with Convergence Guarantees
by: Xiao, Nachuan, et al.
Published: (2023)

On Convergence of Adam for Stochastic Optimization under Relaxed Assumptions
by: Hong, Yusu, et al.
Published: (2024)

Efficient Online Large-Margin Classification via Dual Certificates
by: Ho-Nguyen, Nam, et al.
Published: (2025)

Adam with model exponential moving average is effective for nonconvex optimization
by: Ahn, Kwangjun, et al.
Published: (2024)

Convergence of Steepest Descent and Adam under Non-Uniform Smoothness
by: Vaswani, Sharan, et al.
Published: (2026)

A Semantic-Loss Function Modeling Framework With Task-Oriented Machine Learning Perspectives
by: Nguyen, Ti Ti, et al.
Published: (2025)

From Distributional Robustness to Robust Statistics: A Confidence Sets Perspective
by: Chan, Gabriel, et al.
Published: (2024)

On the Convergence of Adam-Type Algorithm for Bilevel Optimization under Unbounded Smoothness
by: Gong, Xiaochuan, et al.
Published: (2025)

Implicit Bias of AdamW: $\ell_\infty$ Norm Constrained Optimization
by: Xie, Shuo, et al.
Published: (2024)

A Comprehensive Framework for Analyzing the Convergence of Adam: Bridging the Gap with SGD
by: Jin, Ruinan, et al.
Published: (2024)

Muon Outperforms Adam in Tail-End Associative Memory Learning
by: Wang, Shuche, et al.
Published: (2025)

On the $O(\frac{\sqrt{d}}{K^{1/4}})$ Convergence Rate of AdamW Measured by $\ell_1$ Norm
by: Li, Huan, et al.
Published: (2025)

Is your batch size the problem? Revisiting the Adam-SGD gap in language modeling
by: Srećković, Teodora, et al.
Published: (2025)

On the Convergence of Adam under Non-uniform Smoothness: Separability from SGDM and Beyond
by: Wang, Bohan, et al.
Published: (2024)

ODE approximation for the Adam algorithm: General and overparametrized setting
by: Dereich, Steffen, et al.
Published: (2025)

Learning of Linear Dynamical Systems as a Non-Commutative Polynomial Optimization Problem
by: Zhou, Quan, et al.
Published: (2020)

Clipping Improves Adam-Norm and AdaGrad-Norm when the Noise Is Heavy-Tailed
by: Chezhegov, Savelii, et al.
Published: (2024)

Dynamic Regret via Discounted-to-Dynamic Reduction with Applications to Curved Losses and Adam Optimizer
by: Xie, Yan-Feng, et al.
Published: (2026)

Towards Quantifying the Preconditioning Effect of Adam
by: Das, Rudrajit, et al.
Published: (2024)

Fully Unconstrained Online Learning
by: Cutkosky, Ashok, et al.
Published: (2024)

On the Implicit Bias of Adam
by: Cattaneo, Matias D., et al.
Published: (2023)

Upper-Linearizability of Online Non-Monotone DR-Submodular Maximization over Down-Closed Convex Sets
by: Lu, Yiyang, et al.
Published: (2026)

Online Optimization Perspective on First-Order and Zero-Order Decentralized Nonsmooth Nonconvex Stochastic Optimization
by: Sahinoglu, Emre, et al.
Published: (2024)

Safe Online Control-Informed Learning
by: Zhou, Tianyu, et al.
Published: (2025)