Cover Image

On Approximate Computation of Critical Points

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Ahmadi, Amir Ali, Hall, Georgina
Format:	Preprint
Published:	2026
Subjects:	Optimization and Control Computational Complexity Machine Learning Numerical Analysis
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

High Probability Complexity Bounds of Trust-Region Stochastic Sequential Quadratic Programming with Heavy-Tailed Noise
by: Fang, Yuchen, et al.
Published: (2025)

A single-loop SPIDER-type stochastic subgradient method for expectation-constrained nonconvex nonsmooth optimization
by: Liu, Wei, et al.
Published: (2025)

Symmetry & Critical Points
by: Arjevani, Yossi
Published: (2024)

Backtracking New Q-Newton's method, Newton's flow, Voronoi's diagram and Stochastic root finding
by: Fornaess, John Erik, et al.
Published: (2024)

The Computational Complexity of Finding Stationary Points in Non-Convex Optimization
by: Hollender, Alexandros, et al.
Published: (2023)

Optimal Preconditioning is a Geodesically Convex Optimization Problem
by: Doğan, M. Levent, et al.
Published: (2025)

From Cursed to Competitive: Closing the ZO-FO Gap via Input-to-State Stability
by: Farzin, Amir Ali, et al.
Published: (2026)

Solving the Offline and Online Min-Max Problem of Non-smooth Submodular-Concave Functions: A Zeroth-Order Approach
by: Farzin, Amir Ali, et al.
Published: (2026)

Minimisation of Submodular Functions Using Gaussian Zeroth-Order Random Oracles
by: Farzin, Amir Ali, et al.
Published: (2025)

A direct optimization algorithm for input-constrained MPC
by: Wu, Liang, et al.
Published: (2023)

Symmetry & Critical Points for Symmetric Tensor Decomposition Problems
by: Arjevani, Yossi, et al.
Published: (2023)

On the Stability Connection Between Discrete-Time Algorithms and Their Resolution ODEs: Applications to Min-Max Optimisation
by: Farzin, Amir Ali, et al.
Published: (2026)

Differentiable Singular Value Decomposition
by: Kanchi, Rohit, et al.
Published: (2025)

Efficient Algorithms for Regularized Nonnegative Scale-invariant Low-rank Approximation Models
by: Cohen, Jeremy E., et al.
Published: (2024)

A Trust-Region Interior-Point Stochastic Sequential Quadratic Programming Method
by: Fang, Yuchen, et al.
Published: (2026)

WinQ: Accelerating Quantization-Aware Training of Language Models Around Saddle Points
by: Li, Dongyue, et al.
Published: (2026)

Faster Computation of Entropic Optimal Transport via Stable Low Frequency Modes
by: Chhaibi, Reda, et al.
Published: (2025)

Polynomial Scaling is Possible For Neural Operator Approximations of Structured Families of BSDEs
by: Furuya, Takashi, et al.
Published: (2024)

Trust-Region Sequential Quadratic Programming for Stochastic Optimization with Random Models
by: Fang, Yuchen, et al.
Published: (2024)

Modified Loss of Momentum Gradient Descent: Fine-Grained Analysis
by: Cattaneo, Matias D., et al.
Published: (2025)

Online Covariance Matrix Estimation in Sketched Newton Methods
by: Kuang, Wei, et al.
Published: (2025)

Bayesian Optimization on Networks
by: Li, Wenwen, et al.
Published: (2025)

Minimisation of Quasar-Convex Functions Using Random Zeroth-Order Oracles
by: Farzin, Amir Ali, et al.
Published: (2025)

What is a Sketch-and-Precondition Derivation for Low-Rank Approximation? Inverse Power Error or Inverse Power Estimation?
by: Xu, Ruihan, et al.
Published: (2025)

Min-Max Optimisation for Nonconvex-Nonconcave Functions Using a Random Zeroth-Order Extragradient Algorithm
by: Farzin, Amir Ali, et al.
Published: (2025)

Generalized Ellipsoids
by: Ahmadi, Amir Ali, et al.
Published: (2024)

Universal Approximation of Nonlinear Operators and Their Derivatives
by: de Feo, Filippo
Published: (2026)

Transferable Foundation Models for Geometric Tasks on Point Cloud Representations: Geometric Neural Operators
by: Quackenbush, Blaine, et al.
Published: (2025)

Generative Neural Operators of Log-Complexity Can Simultaneously Solve Infinitely Many Convex Programs
by: Kratsios, Anastasis, et al.
Published: (2025)

Stability Preserving Data-driven Models With Latent Dynamics
by: Luo, Yushuang, et al.
Published: (2022)

A Variational Framework for Residual-Based Adaptivity in Neural PDE Solvers and Operator Learning
by: Toscano, Juan Diego, et al.
Published: (2025)

Dynamic Proximal Gradient Algorithms for Schatten-$p$ Quasi-Norm Regularized Problems
by: Shen, Weiping, et al.
Published: (2026)

Why is Normalization Preferred? A Worst-Case Complexity Theory for Stochastically Preconditioned SGD under Heavy-Tailed Noise
by: Fang, Yuchen, et al.
Published: (2026)

Natural Riemannian gradient for learning functional tensor networks
by: Klug, Nikolas, et al.
Published: (2026)

State-Dependent Lyapunov Method for Rank-1 Matrix Factorization
by: Moon, Jaehong
Published: (2026)

Primal-Dual Methods for Nonsmooth Nonconvex Optimization with Orthogonality Constraints
by: Zhu, Linglingzhi, et al.
Published: (2026)

A distributed semismooth Newton based augmented Lagrangian method for distributed optimization
by: Ma, Qihao, et al.
Published: (2026)

Last-Iterate Convergence of Randomized Kaczmarz and SGD with Greedy Step Size
by: Dereziński, Michał, et al.
Published: (2026)

OptEMA: Adaptive Exponential Moving Average for Stochastic Optimization with Zero-Noise Optimality
by: Yuan, Ganzhao
Published: (2026)

Nonlinear model reduction for transport-dominated problems
by: Hesthaven, Jan S., et al.
Published: (2026)