Cover Image

Noise Stability Optimization for Finding Flat Minima: A Hessian-based Regularization Approach

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Zhang, Hongyang R., Li, Dongyue, Ju, Haotian
Format:	Preprint
Published:	2023
Subjects:	Machine Learning Data Structures and Algorithms Optimization and Control
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Learning a Single Neuron Robustly to Distributional Shifts and Adversarial Label Noise
by: Li, Shuyao, et al.
Published: (2024)

Balancing Gradient and Hessian Queries in Non-Convex Optimization
by: Adil, Deeksha, et al.
Published: (2025)

Complexity of Classical Acceleration for $\ell_1$-Regularized PageRank
by: Fountoulakis, Kimon, et al.
Published: (2026)

Multi-LLM Query Optimization
by: Dean, Arlen, et al.
Published: (2026)

Distributionally Robust Optimization with Adversarial Data Contamination
by: Li, Shuyao, et al.
Published: (2025)

Online Bilevel Optimization: Regret Analysis of Online Alternating Gradient Methods
by: Tarzanagh, Davoud Ataee, et al.
Published: (2022)

Breaking the Heavy-Tailed Noise Barrier in Stochastic Optimization Problems
by: Puchkin, Nikita, et al.
Published: (2023)

Negative Momentum for Convex-Concave Optimization
by: Shugart, Henry, et al.
Published: (2026)

Optimal Decentralized Smoothed Online Convex Optimization
by: Bhuyan, Neelkamal, et al.
Published: (2024)

Convex Optimization with Nested Evolving Feasible Sets
by: M., Karthick Krishna, et al.
Published: (2026)

Optimal Bounds for Adversarial Constrained Online Convex Optimization
by: Ferreira, Ricardo N., et al.
Published: (2025)

Non-Euclidean High-Order Smooth Convex Optimization
by: Contreras, Juan Pablo, et al.
Published: (2024)

Gradient-Free Method for Heavily Constrained Nonconvex Optimization
by: Shi, Wanli, et al.
Published: (2024)

Min-Max Optimization Is Strictly Easier Than Variational Inequalities
by: Shugart, Henry, et al.
Published: (2025)

Closing the Computational-Query Depth Gap in Parallel Stochastic Convex Optimization
by: Jambulapati, Arun, et al.
Published: (2024)

Optimization on a Finer Scale: Bounded Local Subgradient Variation Perspective
by: Diakonikolas, Jelena, et al.
Published: (2024)

Accelerated Algorithms for Constrained Nonconvex-Nonconcave Min-Max Optimization and Comonotone Inclusion
by: Cai, Yang, et al.
Published: (2022)

Online Convex Optimization with Switching Cost with Only One Single Gradient Evaluation
by: Shah, Harsh, et al.
Published: (2025)

Infrequent Resolving Algorithm for Online Linear Programming
by: Li, Guokai, et al.
Published: (2024)

Gradient Testing and Estimation by Comparisons
by: Tao, Xiwen, et al.
Published: (2024)

Oracle-based Uniform Sampling from Convex Bodies
by: Dang, Thanh, et al.
Published: (2025)

Isotropic Noise in Stochastic and Quantum Convex Optimization
by: Marsden, Annie, et al.
Published: (2025)

Optimal Scalarizations for Sublinear Hypervolume Regret
by: Zhang, Qiuyi
Published: (2023)

Extended convexity and smoothness and their applications in deep learning
by: Qi, Binchuan, et al.
Published: (2024)

Importance Sparsification for Sinkhorn Algorithm
by: Li, Mengyu, et al.
Published: (2023)

Convergence analysis of wide shallow neural operators within the framework of Neural Tangent Kernel
by: Xu, Xianliang, et al.
Published: (2024)

Low Rank Matrix Completion via Robust Alternating Minimization in Nearly Linear Time
by: Gu, Yuzhou, et al.
Published: (2023)

Combinatorial Sparse PCA Beyond the Spiked Identity Model
by: Kumar, Syamantak, et al.
Published: (2026)

Robust Learning of a Group DRO Neuron
by: Cao, Guyang, et al.
Published: (2026)

Fast Computation of Optimal Transport via Entropy-Regularized Extragradient Methods
by: Li, Gen, et al.
Published: (2023)

Quantum Algorithms and Lower Bounds for Finite-Sum Optimization
by: Zhang, Yexin, et al.
Published: (2024)

Best of Both Worlds Guarantees for Smoothed Online Quadratic Optimization
by: Bhuyan, Neelkamal, et al.
Published: (2023)

Gaussian Cooling and Dikin Walks: The Interior-Point Method for Logconcave Sampling
by: Kook, Yunbum, et al.
Published: (2023)

Online Resource Allocation with Convex-set Machine-Learned Advice
by: Golrezaei, Negin, et al.
Published: (2023)

Learning to Schedule in Parallel-Server Queues with Stochastic Bilinear Rewards
by: Kim, Jung-hun, et al.
Published: (2021)

Constrained and Composite Sampling via Proximal Sampler
by: Dang, Thanh, et al.
Published: (2026)

Online Linear Programming with Replenishment
by: Chen, Yuze, et al.
Published: (2026)

Learning-Augmented Algorithms for Online Concave Packing and Convex Covering Problems
by: Grigorescu, Elena, et al.
Published: (2024)

Learning Mixtures of Spherical Gaussians via Fourier Analysis
by: Chakraborty, Somnath, et al.
Published: (2020)

Negative Stepsizes Make Gradient-Descent-Ascent Converge
by: Shugart, Henry, et al.
Published: (2025)