Copertina

Smoothing the Edges: Smooth Optimization for Sparse Regularization using Hadamard Overparametrization

Fuente: arXiv

Salvato in:

Dettagli Bibliografici
Autori principali:	Kolb, Chris, Müller, Christian L., Bischl, Bernd, Rügamer, David
Natura:	Preprint
Pubblicazione:	2023
Soggetti:	Machine Learning Optimization and Control
Accesso online:	Acceder al recurso
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

Smooth Quasar-Convex Optimization with Constraints
di: Martínez-Rubio, David
Pubblicazione: (2025)

Deep Weight Factorization: Sparse Learning Through the Lens of Artificial Symmetries
di: Kolb, Chris, et al.
Pubblicazione: (2025)

A Retrospective Approximation Approach for Smooth Stochastic Optimization
di: Newton, David, et al.
Pubblicazione: (2021)

Gradient-Normalized Smoothness for Optimization with Approximate Hessians
di: Semenov, Andrei, et al.
Pubblicazione: (2025)

Probabilistic Smoothing with Ratio-Monotone Transforms for Global Optimization
di: Jang, Kukyoung, et al.
Pubblicazione: (2026)

Dynamic Anisotropic Smoothing for Noisy Derivative-Free Optimization
di: Reifenstein, Sam, et al.
Pubblicazione: (2024)

Decentralized Stochastic Nonconvex Optimization under the Relaxed Smoothness
di: Luo, Luo, et al.
Pubblicazione: (2025)

Stochastic Non-Smooth Convex Optimization with Unbounded Gradients
di: Kovalev, Dmitry
Pubblicazione: (2026)

On the Complexity of Decentralized Smooth Nonconvex Finite-Sum Optimization
di: Luo, Luo, et al.
Pubblicazione: (2022)

Efficiently Escaping Saddle Points under Generalized Smoothness via Self-Bounding Regularity
di: Cao, Daniel Yiming, et al.
Pubblicazione: (2025)

Faster Gradient Methods for Highly-Smooth Stochastic Bilevel Optimization
di: Chen, Lesi, et al.
Pubblicazione: (2025)

Gradient-Variation Online Adaptivity for Accelerated Optimization with Hölder Smoothness
di: Zhao, Yuheng, et al.
Pubblicazione: (2025)

An Accelerated Gradient Method for Convex Smooth Simple Bilevel Optimization
di: Cao, Jincheng, et al.
Pubblicazione: (2024)

An Accelerated Algorithm for Stochastic Bilevel Optimization under Unbounded Smoothness
di: Gong, Xiaochuan, et al.
Pubblicazione: (2024)

Federated Optimization of Smooth Loss Functions
di: Jadbabaie, Ali, et al.
Pubblicazione: (2022)

Improving Online-to-Nonconvex Conversion for Smooth Optimization via Double Optimism
di: Patitucci, Francisco, et al.
Pubblicazione: (2025)

Adaptive Gradient Normalization and Independent Sampling for (Stochastic) Generalized-Smooth Optimization
di: Yang, Yufeng, et al.
Pubblicazione: (2024)

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

On the Complexity of Finite-Sum Smooth Optimization under the Polyak-Łojasiewicz Condition
di: Bai, Yunyan, et al.
Pubblicazione: (2024)

(Almost) Smooth Sailing: Towards Numerical Stability of Neural Networks Through Differentiable Regularization of the Condition Number
di: Nenov, Rossen, et al.
Pubblicazione: (2024)

Provably Convergent Decentralized Optimization over Directed Graphs under Generalized Smoothness
di: Bo, Yanan, et al.
Pubblicazione: (2026)

Stochastic Smoothed Primal-Dual Algorithms for Nonconvex Optimization with Linear Inequality Constraints
di: Huang, Ruichuan, et al.
Pubblicazione: (2025)

Bilevel Optimization under Unbounded Smoothness: A New Algorithm and Convergence Analysis
di: Hao, Jie, et al.
Pubblicazione: (2024)

Adaptive Matrix Online Learning through Smoothing with Guarantees for Nonsmooth Nonconvex Optimization
di: Jiang, Ruichen, et al.
Pubblicazione: (2026)

AdaGrad under Anisotropic Smoothness
di: Liu, Yuxing, et al.
Pubblicazione: (2024)

Differentiable Sparsity via $D$-Gating: Simple and Versatile Structured Penalization
di: Kolb, Chris, et al.
Pubblicazione: (2025)

A Smoothing Algorithm for l1 Support Vector Machines
di: Emirahmetoglu, Ibrahim, et al.
Pubblicazione: (2023)

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

Using Stochastic Gradient Descent to Smooth Nonconvex Functions: Analysis of Implicit Graduated Optimization
di: Sato, Naoki, et al.
Pubblicazione: (2023)

High Probability Complexity Bounds for Non-Smooth Stochastic Optimization with Heavy-Tailed Noise
di: Gorbunov, Eduard, et al.
Pubblicazione: (2021)

Methods for Convex $(L_0,L_1)$-Smooth Optimization: Clipping, Acceleration, and Adaptivity
di: Gorbunov, Eduard, et al.
Pubblicazione: (2024)

Methods with Local Steps and Random Reshuffling for Generally Smooth Non-Convex Federated Optimization
di: Demidovich, Yury, et al.
Pubblicazione: (2024)

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

A Stochastic Quasi-Newton Method for Non-convex Optimization with Non-uniform Smoothness
di: Sun, Zhenyu, et al.
Pubblicazione: (2024)

MGDA Converges under Generalized Smoothness, Provably
di: Zhang, Qi, et al.
Pubblicazione: (2024)

On the Interpolation Effect of Score Smoothing in Diffusion Models
di: Chen, Zhengdao
Pubblicazione: (2025)

Directional Smoothness and Gradient Methods: Convergence and Adaptivity
di: Mishkin, Aaron, et al.
Pubblicazione: (2024)

On Constraints in First-Order Optimization: A View from Non-Smooth Dynamical Systems
di: Muehlebach, Michael, et al.
Pubblicazione: (2021)

A Local Polyak-Lojasiewicz and Descent Lemma of Gradient Descent For Overparametrized Linear Models
di: Xu, Ziqing, et al.
Pubblicazione: (2025)

A Nearly Optimal Single Loop Algorithm for Stochastic Bilevel Optimization under Unbounded Smoothness
di: Gong, Xiaochuan, et al.
Pubblicazione: (2024)