Cover Image

Fast Stochastic Composite Minimization and an Accelerated Frank-Wolfe Algorithm under Parallelization

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Dubois-Taine, Benjamin, Bach, Francis, Berthet, Quentin, Taylor, Adrien
Format:	Preprint
Published:	2022
Subjects:	Optimization and Control Machine Learning
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Towards Noise-adaptive, Problem-adaptive (Accelerated) Stochastic Gradient Descent
by: Vaswani, Sharan, et al.
Published: (2021)

Frank-Wolfe meets Shapley-Folkman: a systematic approach for solving nonconvex separable problems with linear constraints
by: Dubois-Taine, Benjamin, et al.
Published: (2024)

Accelerated Frank-Wolfe Algorithms: Complementarity Conditions and Sparsity
by: Garber, Dan
Published: (2025)

Stochastic Compositional Optimization via Hybrid Momentum Frank--Wolfe
by: Chayti, El Mahdi
Published: (2026)

Two-stage stochastic algorithm for solving large-scale (non)-convex separable optimization problems under affine constraints
by: Dubois-Taine, Benjamin, et al.
Published: (2026)

Beyond Short Steps in Frank-Wolfe Algorithms
by: Martínez-Rubio, David, et al.
Published: (2025)

Lions and Muons: Optimization via Stochastic Frank-Wolfe
by: Sfyraki, Maria-Eleni, et al.
Published: (2025)

Linear Convergence of the Frank-Wolfe Algorithm over Product Polytopes
by: Iommazzo, Gabriele, et al.
Published: (2025)

Scalable DC Optimization via Adaptive Frank-Wolfe Algorithms
by: Pokutta, Sebastian
Published: (2025)

Using Taylor-Approximated Gradients to Improve the Frank-Wolfe Method for Empirical Risk Minimization
by: Xiong, Zikai, et al.
Published: (2022)

Projected Forward Gradient-Guided Frank-Wolfe Algorithm via Variance Reduction
by: Rostami, M., et al.
Published: (2024)

Optimal Algorithms for Stochastic Complementary Composite Minimization
by: d'Aspremont, Alexandre, et al.
Published: (2022)

A Randomized Linearly Convergent Frank-Wolfe-type Method for Smooth Convex Minimization over the Spectrahedron
by: Garber, Dan
Published: (2025)

The Surprising Agreement Between Convex Optimization Theory and Learning-Rate Scheduling for Large Model Training
by: Schaipp, Fabian, et al.
Published: (2025)

Compression-aware Training of Neural Networks using Frank-Wolfe
by: Zimmer, Max, et al.
Published: (2022)

Don't Be Greedy, Just Relax! Pruning LLMs via Frank-Wolfe
by: Roux, Christophe, et al.
Published: (2025)

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

Scaling Laws for Gradient Descent and Sign Descent for Linear Bigram Models under Zipf's Law
by: Kunstner, Frederik, et al.
Published: (2025)

Scalable Frank-Wolfe on Generalized Self-concordant Functions via Simple Steps
by: Carderera, Alejandro, et al.
Published: (2021)

Sarah Frank-Wolfe: Methods for Constrained Optimization with Best Rates and Practical Features
by: Beznosikov, Aleksandr, et al.
Published: (2023)

On the Effectiveness of the z-Transform Method in Quadratic Optimization
by: Bach, Francis
Published: (2025)

A Convex Loss Function for Set Prediction with Optimal Trade-offs Between Size and Conditional Coverage
by: Bach, Francis
Published: (2025)

Revisiting Frank-Wolfe for Structured Nonconvex Optimization
by: Maskan, Hoomaan, et al.
Published: (2025)

SOREL: A Stochastic Algorithm for Spectral Risks Minimization
by: Ge, Yuze, et al.
Published: (2024)

A Tight Theory of Error Feedback Algorithms in Distributed Optimization
by: Thomsen, Daniel Berg, et al.
Published: (2026)

Exponential Convergence of (Stochastic) Gradient Descent for Separable Logistic Regression
by: Kale, Sacchit, et al.
Published: (2026)

Convex mixed-integer optimization with Frank-Wolfe methods
by: Hendrych, Deborah, et al.
Published: (2022)

Acceleration Methods
by: d'Aspremont, Alexandre, et al.
Published: (2021)

Stochastic Variance-Reduced Newton: Accelerating Finite-Sum Minimization with Large Batches
by: Dereziński, Michał
Published: (2022)

SHANG++: Robust Stochastic Acceleration under Multiplicative Noise
by: Yu, Yaxin, et al.
Published: (2026)

A New Convergence Analysis of Two Stochastic Frank-Wolfe Algorithms
by: Boonsiriphatthanajaroen, Natthawut, et al.
Published: (2025)

A Spectral Framework for Closed-Form Relative Density Estimation
by: Bach, Francis
Published: (2026)

Faster Convergence of Stochastic Accelerated Gradient Descent under Interpolation
by: Mishkin, Aaron, et al.
Published: (2024)

Auto-Conditioned Frank-Wolfe Algorithms
by: Giang-Tran, Khanh-Hung, et al.
Published: (2026)

Iteratively Reweighted Least Squares for Phase Unwrapping
by: Dubois-Taine, Benjamin, et al.
Published: (2024)

Stochastic Origin Frank-Wolfe for traffic assignment
by: Ignashin, Igor, et al.
Published: (2025)

Robustness of the Frank-Wolfe Method under Inexact Oracles and the Cost of Linear Minimization
by: Hu, Tao
Published: (2025)

High-Probability Convergence for Composite and Distributed Stochastic Minimization and Variational Inequalities with Heavy-Tailed Noise
by: Gorbunov, Eduard, et al.
Published: (2023)

Accelerated Convergence of Stochastic Heavy Ball Method under Anisotropic Gradient Noise
by: Pan, Rui, et al.
Published: (2023)

Parameter-Free Algorithms for Performative Regret Minimization under Decision-Dependent Distributions
by: Park, Sungwoo, et al.
Published: (2024)