A Sketch-and-Project Analysis of Subsampled Natural Gradient Algorithms
Fuente:
arXiv
Saved in:
| Main Authors: | Goldshlager, Gil, Hu, Jiang, Lin, Lin |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Worth Their Weight: Randomized and Regularized Block Kaczmarz Algorithms without Preprocessing
by: Goldshlager, Gil, et al.
Published: (2025)
by: Goldshlager, Gil, et al.
Published: (2025)
Turbocharging Gaussian Process Inference with Approximate Sketch-and-Project
by: Rathore, Pratik, et al.
Published: (2025)
by: Rathore, Pratik, et al.
Published: (2025)
Two-Timescale Gradient Descent Ascent Algorithms for Nonconvex Minimax Optimization
by: Lin, Tianyi, et al.
Published: (2024)
by: Lin, Tianyi, et al.
Published: (2024)
Reusing Historical Trajectories in Natural Policy Gradient via Importance Sampling: Convergence and Convergence Rate
by: Lin, Yifan, et al.
Published: (2024)
by: Lin, Yifan, et al.
Published: (2024)
Adaptive Moment Estimation Optimization Algorithm Using Projection Gradient for Deep Learning
by: Li, Yongqi, et al.
Published: (2025)
by: Li, Yongqi, et al.
Published: (2025)
Projected Forward Gradient-Guided Frank-Wolfe Algorithm via Variance Reduction
by: Rostami, M., et al.
Published: (2024)
by: Rostami, M., et al.
Published: (2024)
Subsampled Ensemble Can Improve Generalization Tail Exponentially
by: Qian, Huajie, et al.
Published: (2024)
by: Qian, Huajie, et al.
Published: (2024)
Federated Learning on Riemannian Manifolds: A Gradient-Free Projection-Based Approach
by: Wang, Hongye, et al.
Published: (2025)
by: Wang, Hongye, et al.
Published: (2025)
Zeroth-Order primal-dual Alternating Projection Gradient Algorithms for Nonconvex Minimax Problems with Coupled linear Constraints
by: Zhang, Huiling, et al.
Published: (2024)
by: Zhang, Huiling, et al.
Published: (2024)
Sketch-and-Project Meets Newton Method: Global $\mathcal O(k^{-2})$ Convergence with Low-Rank Updates
by: Hanzely, Slavomír
Published: (2023)
by: Hanzely, Slavomír
Published: (2023)
Recurrent Natural Policy Gradient for POMDPs
by: Cayci, Semih, et al.
Published: (2024)
by: Cayci, Semih, et al.
Published: (2024)
Towards An Efficient Approach for the Nonconvex $\ell_p$ Ball Projection: Algorithm and Analysis
by: Yang, Xiangyu, et al.
Published: (2021)
by: Yang, Xiangyu, et al.
Published: (2021)
Natural Hypergradient Descent: Algorithm Design, Convergence Analysis, and Parallel Implementation
by: Kong, Deyi, et al.
Published: (2026)
by: Kong, Deyi, et al.
Published: (2026)
Accelerated Gradient Tracking over Time-varying Graphs for Decentralized Optimization
by: Li, Huan, et al.
Published: (2021)
by: Li, Huan, et al.
Published: (2021)
An Adaptive Stochastic Gradient Method with Non-negative Gauss-Newton Stepsizes
by: Orvieto, Antonio, et al.
Published: (2024)
by: Orvieto, Antonio, et al.
Published: (2024)
Learning Provably Improves the Convergence of Gradient Descent
by: Song, Qingyu, et al.
Published: (2025)
by: Song, Qingyu, et al.
Published: (2025)
Quantitative Convergence Analysis of Projected Stochastic Gradient Descent for Non-Convex Losses via the Goldstein Subdifferential
by: Zheng, Yuping, et al.
Published: (2025)
by: Zheng, Yuping, et al.
Published: (2025)
On the Inherent Privacy of Zeroth Order Projected Gradient Descent
by: Gupta, Devansh, et al.
Published: (2025)
by: Gupta, Devansh, et al.
Published: (2025)
Mitigating Forgetting in Continual Learning with Selective Gradient Projection
by: Singh, Anika, et al.
Published: (2026)
by: Singh, Anika, et al.
Published: (2026)
Shuffling Momentum Gradient Algorithm for Convex Optimization
by: Tran, Trang H., et al.
Published: (2024)
by: Tran, Trang H., et al.
Published: (2024)
On Gradient Descent Ascent for Nonconvex-Concave Minimax Problems
by: Lin, Tianyi, et al.
Published: (2019)
by: Lin, Tianyi, et al.
Published: (2019)
Gauss-Newton Natural Gradient Descent for Shape Learning
by: King, James, et al.
Published: (2026)
by: King, James, et al.
Published: (2026)
AdaGrad-Diff: A New Version of the Adaptive Gradient Algorithm
by: Bojovic, Matia, et al.
Published: (2026)
by: Bojovic, Matia, et al.
Published: (2026)
Convergence Properties of Natural Gradient Descent for Minimizing KL Divergence
by: Datar, Adwait, et al.
Published: (2025)
by: Datar, Adwait, et al.
Published: (2025)
Optimal Guarantees for Algorithmic Reproducibility and Gradient Complexity in Convex Optimization
by: Zhang, Liang, et al.
Published: (2023)
by: Zhang, Liang, et al.
Published: (2023)
Faster Gradient-Free Algorithms for Nonsmooth Nonconvex Stochastic Optimization
by: Chen, Lesi, et al.
Published: (2023)
by: Chen, Lesi, et al.
Published: (2023)
Natural Policy Gradient as Doubly Smoothed Policy Iteration: A Bellman-Operator Framework
by: Nanda, Phalguni, et al.
Published: (2026)
by: Nanda, Phalguni, et al.
Published: (2026)
An Energy-Based Self-Adaptive Learning Rate for Stochastic Gradient Descent: Enhancing Unconstrained Optimization with VAV method
by: Zhang, Jiahao, et al.
Published: (2024)
by: Zhang, Jiahao, et al.
Published: (2024)
Randomized Block-Coordinate Optimistic Gradient Algorithms for Root-Finding Problems
by: Tran-Dinh, Quoc, et al.
Published: (2023)
by: Tran-Dinh, Quoc, et al.
Published: (2023)
Dual Natural Gradient Descent for Scalable Training of Physics-Informed Neural Networks
by: Jnini, Anas, et al.
Published: (2025)
by: Jnini, Anas, et al.
Published: (2025)
Linear Convergence of Entropy-Regularized Natural Policy Gradient with Linear Function Approximation
by: Cayci, Semih, et al.
Published: (2021)
by: Cayci, Semih, et al.
Published: (2021)
Global Convergence of Natural Policy Gradient with Hessian-aided Momentum Variance Reduction
by: Feng, Jie, et al.
Published: (2024)
by: Feng, Jie, et al.
Published: (2024)
Elementary Analysis of Policy Gradient Methods
by: Liu, Jiacai, et al.
Published: (2024)
by: Liu, Jiacai, et al.
Published: (2024)
A Variance-Reduced Stochastic Gradient Tracking Algorithm for Decentralized Optimization with Orthogonality Constraints
by: Wang, Lei, et al.
Published: (2022)
by: Wang, Lei, et al.
Published: (2022)
Stochastic Approximation with Block Coordinate Optimal Stepsizes
by: Jiang, Tao, et al.
Published: (2025)
by: Jiang, Tao, et al.
Published: (2025)
GeoAdaLer: Geometric Insights into Adaptive Stochastic Gradient Descent Algorithms
by: Eleh, Chinedu, et al.
Published: (2024)
by: Eleh, Chinedu, et al.
Published: (2024)
Stochastic Gradient Descent with Strategic Querying
by: Jiang, Nanfei, et al.
Published: (2025)
by: Jiang, Nanfei, et al.
Published: (2025)
Can We Remove the Square-Root in Adaptive Gradient Methods? A Second-Order Perspective
by: Lin, Wu, et al.
Published: (2024)
by: Lin, Wu, et al.
Published: (2024)
Natural Policy Gradient and Actor Critic Methods for Constrained Multi-Task Reinforcement Learning
by: Zeng, Sihan, et al.
Published: (2024)
by: Zeng, Sihan, et al.
Published: (2024)
Unbiased Gradient Low-Rank Projection
by: Pan, Rui, et al.
Published: (2025)
by: Pan, Rui, et al.
Published: (2025)
Similar Items
-
Worth Their Weight: Randomized and Regularized Block Kaczmarz Algorithms without Preprocessing
by: Goldshlager, Gil, et al.
Published: (2025) -
Turbocharging Gaussian Process Inference with Approximate Sketch-and-Project
by: Rathore, Pratik, et al.
Published: (2025) -
Two-Timescale Gradient Descent Ascent Algorithms for Nonconvex Minimax Optimization
by: Lin, Tianyi, et al.
Published: (2024) -
Reusing Historical Trajectories in Natural Policy Gradient via Importance Sampling: Convergence and Convergence Rate
by: Lin, Yifan, et al.
Published: (2024) -
Adaptive Moment Estimation Optimization Algorithm Using Projection Gradient for Deep Learning
by: Li, Yongqi, et al.
Published: (2025)