Random Subspace Cubic-Regularization Methods, with Applications to Low-Rank Functions
Fuente:
arXiv
Guardado en:
| Autores principales: | Cartis, Coralia, Shao, Zhen, Tansley, Edward |
|---|---|
| Formato: | Preprint |
| Publicado: |
2025
|
| Materias: | |
| Acceso en línea: | |
| Etiquetas: |
Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
|
Ejemplares similares
On Global Rates for Regularization Methods based on Secant Derivative Approximations
por: Cartis, Coralia, et al.
Publicado: (2025)
por: Cartis, Coralia, et al.
Publicado: (2025)
Global Convergence of High-Order Regularization Methods with Sums-of-Squares Taylor Models
por: Zhu, Wenqi, et al.
Publicado: (2024)
por: Zhu, Wenqi, et al.
Publicado: (2024)
Scalable Second-Order Optimization Algorithms for Minimizing Low-rank Functions
por: Tansley, Edward, et al.
Publicado: (2025)
por: Tansley, Edward, et al.
Publicado: (2025)
Global Optimality Characterizations and Algorithms for Minimizing Quartically-Regularized Third-Order Taylor Polynomials
por: Zhu, Wenqi, et al.
Publicado: (2025)
por: Zhu, Wenqi, et al.
Publicado: (2025)
Nonlinear Dimensionality Reduction Techniques for Bayesian Optimization
por: Long, Luo, et al.
Publicado: (2025)
por: Long, Luo, et al.
Publicado: (2025)
Dimensionality Reduction Techniques for Global Bayesian Optimisation
por: Long, Luo, et al.
Publicado: (2024)
por: Long, Luo, et al.
Publicado: (2024)
Second-order methods for quartically-regularised cubic polynomials, with applications to high-order tensor methods
por: Cartis, Coralia, et al.
Publicado: (2023)
por: Cartis, Coralia, et al.
Publicado: (2023)
Tensor-based Dinkelbach method for computing generalized tensor eigenvalues and its applications
por: Chen, Haibin, et al.
Publicado: (2025)
por: Chen, Haibin, et al.
Publicado: (2025)
Symmetric Rank-One Quasi-Newton Methods for Deep Learning Using Cubic Regularization
por: Ranganath, Aditya, et al.
Publicado: (2025)
por: Ranganath, Aditya, et al.
Publicado: (2025)
Worth Their Weight: Randomized and Regularized Block Kaczmarz Algorithms without Preprocessing
por: Goldshlager, Gil, et al.
Publicado: (2025)
por: Goldshlager, Gil, et al.
Publicado: (2025)
Cubic regularized subspace Newton for non-convex optimization
por: Zhao, Jim, et al.
Publicado: (2024)
por: Zhao, Jim, et al.
Publicado: (2024)
State-Dependent Lyapunov Method for Rank-1 Matrix Factorization
por: Moon, Jaehong
Publicado: (2026)
por: Moon, Jaehong
Publicado: (2026)
Learning Regularization Functionals for Inverse Problems: A Comparative Study
por: Hertrich, Johannes, et al.
Publicado: (2025)
por: Hertrich, Johannes, et al.
Publicado: (2025)
Faster Randomized Methods for Orthogonality Constrained Problems
por: Shustin, Boris, et al.
Publicado: (2021)
por: Shustin, Boris, et al.
Publicado: (2021)
Efficient Algorithms for Regularized Nonnegative Scale-invariant Low-rank Approximation Models
por: Cohen, Jeremy E., et al.
Publicado: (2024)
por: Cohen, Jeremy E., et al.
Publicado: (2024)
Quadratic Objective Perturbation: Curvature-Based Differential Privacy
por: Cortild, Daniel, et al.
Publicado: (2026)
por: Cortild, Daniel, et al.
Publicado: (2026)
Minimisation of Submodular Functions Using Gaussian Zeroth-Order Random Oracles
por: Farzin, Amir Ali, et al.
Publicado: (2025)
por: Farzin, Amir Ali, et al.
Publicado: (2025)
Fundamental Bias in Inverting Random Sampling Matrices with Application to Sub-sampled Newton
por: Niu, Chengmei, et al.
Publicado: (2025)
por: Niu, Chengmei, et al.
Publicado: (2025)
Randomized Subspace Derivative-Free Optimization with Quadratic Models and Second-Order Convergence
por: Cartis, Coralia, et al.
Publicado: (2024)
por: Cartis, Coralia, et al.
Publicado: (2024)
Higher Order Reduced Rank Regression
por: Greenberg, Leia, et al.
Publicado: (2025)
por: Greenberg, Leia, et al.
Publicado: (2025)
The Rank-1 Completion Problem for Cubic Tensors
por: Zhou, Jinling, et al.
Publicado: (2024)
por: Zhou, Jinling, et al.
Publicado: (2024)
Dynamic Proximal Gradient Algorithms for Schatten-$p$ Quasi-Norm Regularized Problems
por: Shen, Weiping, et al.
Publicado: (2026)
por: Shen, Weiping, et al.
Publicado: (2026)
Acceleration Methods
por: d'Aspremont, Alexandre, et al.
Publicado: (2021)
por: d'Aspremont, Alexandre, et al.
Publicado: (2021)
Last-Iterate Convergence of Randomized Kaczmarz and SGD with Greedy Step Size
por: Dereziński, Michał, et al.
Publicado: (2026)
por: Dereziński, Michał, et al.
Publicado: (2026)
A Parameter-Free First-Order Algorithm for Non-Convex Optimization with $\tilde{\mkern1mu O}(ε^{-5/3})$ Global Rate
por: Xiong, Sichao, et al.
Publicado: (2026)
por: Xiong, Sichao, et al.
Publicado: (2026)
Adaptive Proximal Gradient Method for Convex Optimization
por: Malitsky, Yura, et al.
Publicado: (2023)
por: Malitsky, Yura, et al.
Publicado: (2023)
A Globally Convergent Third-Order Newton Method via Unified Semidefinite Programming Subproblems
por: Cai, Yubo, et al.
Publicado: (2026)
por: Cai, Yubo, et al.
Publicado: (2026)
Stochastic Langevin Differential Inclusions with Applications to Machine Learning
por: Difonzo, Fabio V., et al.
Publicado: (2022)
por: Difonzo, Fabio V., et al.
Publicado: (2022)
Primal-Dual Methods for Nonsmooth Nonconvex Optimization with Orthogonality Constraints
por: Zhu, Linglingzhi, et al.
Publicado: (2026)
por: Zhu, Linglingzhi, et al.
Publicado: (2026)
Minimisation of Quasar-Convex Functions Using Random Zeroth-Order Oracles
por: Farzin, Amir Ali, et al.
Publicado: (2025)
por: Farzin, Amir Ali, et al.
Publicado: (2025)
Fast Unconstrained Optimization via Hessian Averaging and Adaptive Gradient Sampling Methods
por: O'Leary-Roseberry, Thomas, et al.
Publicado: (2024)
por: O'Leary-Roseberry, Thomas, et al.
Publicado: (2024)
Adaptive Lipschitz-Free Conditional Gradient Methods for Stochastic Composite Nonconvex Optimization
por: Yuan, Ganzhao
Publicado: (2026)
por: Yuan, Ganzhao
Publicado: (2026)
A Trust-Region Interior-Point Stochastic Sequential Quadratic Programming Method
por: Fang, Yuchen, et al.
Publicado: (2026)
por: Fang, Yuchen, et al.
Publicado: (2026)
The Nondecreasing Rank
por: McCormack, Andrew
Publicado: (2025)
por: McCormack, Andrew
Publicado: (2025)
Shape Derivative-Informed Neural Operators with Application to Risk-Averse Shape Optimization
por: Gong, Xindi, et al.
Publicado: (2026)
por: Gong, Xindi, et al.
Publicado: (2026)
A Block Coordinate Descent Method for Nonsmooth Composite Optimization under Orthogonality Constraints
por: Yuan, Ganzhao
Publicado: (2023)
por: Yuan, Ganzhao
Publicado: (2023)
On the Convergence of the Gradient Descent Method with Stochastic Fixed-point Rounding Errors under the Polyak-Lojasiewicz Inequality
por: Xia, Lu, et al.
Publicado: (2023)
por: Xia, Lu, et al.
Publicado: (2023)
Approaching Optimality for Solving Dense Linear Systems with Low-Rank Structure
por: Dereziński, Michał, et al.
Publicado: (2025)
por: Dereziński, Michał, et al.
Publicado: (2025)
A Natural Primal-Dual Hybrid Gradient Method for Adversarial Neural Network Training on Solving Partial Differential Equations
por: Liu, Shu, et al.
Publicado: (2024)
por: Liu, Shu, et al.
Publicado: (2024)
Generalization Bounds for Sparse Random Feature Expansions
por: Hashemi, Abolfazl, et al.
Publicado: (2021)
por: Hashemi, Abolfazl, et al.
Publicado: (2021)
Ejemplares similares
-
On Global Rates for Regularization Methods based on Secant Derivative Approximations
por: Cartis, Coralia, et al.
Publicado: (2025) -
Global Convergence of High-Order Regularization Methods with Sums-of-Squares Taylor Models
por: Zhu, Wenqi, et al.
Publicado: (2024) -
Scalable Second-Order Optimization Algorithms for Minimizing Low-rank Functions
por: Tansley, Edward, et al.
Publicado: (2025) -
Global Optimality Characterizations and Algorithms for Minimizing Quartically-Regularized Third-Order Taylor Polynomials
por: Zhu, Wenqi, et al.
Publicado: (2025) -
Nonlinear Dimensionality Reduction Techniques for Bayesian Optimization
por: Long, Luo, et al.
Publicado: (2025)