Stochastic Frank-Wolfe: Unified Analysis and Zoo of Special Cases
Fuente:
arXiv
Saved in:
| Main Authors: | Nazykov, Ruslan, Shestakov, Aleksandr, Solodkin, Vladimir, Beznosikov, Aleksandr, Gidel, Gauthier, Gasnikov, Alexander |
|---|---|
| Format: | Preprint |
| Published: |
2024
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Sarah Frank-Wolfe: Methods for Constrained Optimization with Best Rates and Practical Features
by: Beznosikov, Aleksandr, et al.
Published: (2023)
by: Beznosikov, Aleksandr, et al.
Published: (2023)
Accelerated Stochastic Gradient Method with Applications to Consensus Problem in Markov-Varying Networks
by: Solodkin, Vladimir, et al.
Published: (2024)
by: Solodkin, Vladimir, et al.
Published: (2024)
Methods for Optimization Problems with Markovian Stochasticity and Non-Euclidean Geometry
by: Solodkin, Vladimir, et al.
Published: (2024)
by: Solodkin, Vladimir, et al.
Published: (2024)
Unified Theory of Adaptive Variance Reduction
by: Shestakov, Aleksandr, et al.
Published: (2025)
by: Shestakov, Aleksandr, et al.
Published: (2025)
Methods for Solving Variational Inequalities with Markovian Stochasticity
by: Solodkin, Vladimir, et al.
Published: (2024)
by: Solodkin, Vladimir, et al.
Published: (2024)
Optimal Analysis of Method with Batching for Monotone Stochastic Finite-Sum Variational Inequalities
by: Pichugin, Alexander, et al.
Published: (2024)
by: Pichugin, Alexander, et al.
Published: (2024)
Adaptive Regularized Newton Method with Inexact Hessian
by: Shestakov, Aleksandr, et al.
Published: (2025)
by: Shestakov, Aleksandr, et al.
Published: (2025)
Gradient-Free Approaches is a Key to an Efficient Interaction with Markovian Stochasticity
by: Prokhorov, Boris, et al.
Published: (2026)
by: Prokhorov, Boris, et al.
Published: (2026)
WeightLoRA: Keep Only Necessary Adapters
by: Veprikov, Andrey, et al.
Published: (2025)
by: Veprikov, Andrey, et al.
Published: (2025)
Markovian Compression: Looking to the Past Helps Accelerate the Future
by: Veprikov, Andrey, et al.
Published: (2026)
by: Veprikov, Andrey, et al.
Published: (2026)
Method with Batching for Stochastic Finite-Sum Variational Inequalities in Non-Euclidean Setting
by: Pichugin, Alexander, et al.
Published: (2024)
by: Pichugin, Alexander, et al.
Published: (2024)
Power of Generalized Smoothness in Stochastic Convex Optimization: First- and Zero-Order Algorithms
by: Lobanov, Aleksandr, et al.
Published: (2025)
by: Lobanov, Aleksandr, et al.
Published: (2025)
Exploring New Frontiers in Vertical Federated Learning: the Role of Saddle Point Reformulation
by: Beznosikov, Aleksandr, et al.
Published: (2026)
by: Beznosikov, Aleksandr, et al.
Published: (2026)
Extragradient Sliding for Composite Non-Monotone Variational Inequalities
by: Emelyanov, Roman, et al.
Published: (2024)
by: Emelyanov, Roman, et al.
Published: (2024)
Local SGD for Near-Quadratic Problems: Improving Convergence under Unconstrained Noise Conditions
by: Sadchikov, Andrey, et al.
Published: (2024)
by: Sadchikov, Andrey, et al.
Published: (2024)
Accelerated Methods with Compression for Horizontal and Vertical Federated Learning
by: Stanko, Sergey, et al.
Published: (2024)
by: Stanko, Sergey, et al.
Published: (2024)
Distributed Saddle-Point Problems: Lower Bounds, Near-Optimal and Robust Algorithms
by: Beznosikov, Aleksandr, et al.
Published: (2020)
by: Beznosikov, Aleksandr, et al.
Published: (2020)
Optimal Data Splitting in Distributed Optimization for Machine Learning
by: Medyakov, Daniil, et al.
Published: (2024)
by: Medyakov, Daniil, et al.
Published: (2024)
The Black-Box Optimization Problem: Zero-Order Accelerated Stochastic Method via Kernel Approximation
by: Lobanov, Aleksandr, et al.
Published: (2023)
by: Lobanov, Aleksandr, et al.
Published: (2023)
Bregman Proximal Method for Efficient Communications under Similarity
by: Beznosikov, Aleksandr, et al.
Published: (2023)
by: Beznosikov, Aleksandr, et al.
Published: (2023)
Accelerated Zero-Order SGD Method for Solving the Black Box Optimization Problem under "Overparametrization" Condition
by: Lobanov, Aleksandr, et al.
Published: (2023)
by: Lobanov, Aleksandr, et al.
Published: (2023)
Similarity, Compression and Local Steps: Three Pillars of Efficient Communications for Distributed Variational Inequalities
by: Beznosikov, Aleksandr, et al.
Published: (2023)
by: Beznosikov, Aleksandr, et al.
Published: (2023)
About some works of Boris Polyak on convergence of gradient methods and their development
by: Ablaev, Seydamet, et al.
Published: (2023)
by: Ablaev, Seydamet, et al.
Published: (2023)
One-Point Feedback for Composite Optimization with Applications to Distributed and Federated Learning
by: Beznosikov, Aleksandr, et al.
Published: (2021)
by: Beznosikov, Aleksandr, et al.
Published: (2021)
Activations and Gradients Compression for Model-Parallel Training
by: Rudakov, Mikhail, et al.
Published: (2024)
by: Rudakov, Mikhail, et al.
Published: (2024)
Randomized gradient-free methods in convex optimization
by: Gasnikov, Alexander, et al.
Published: (2022)
by: Gasnikov, Alexander, et al.
Published: (2022)
Decentralized Finite-Sum Optimization over Time-Varying Networks
by: Metelev, Dmitry, et al.
Published: (2024)
by: Metelev, Dmitry, et al.
Published: (2024)
Acceleration Exists! Optimization Problems When Oracle Can Only Compare Objective Function Values
by: Lobanov, Aleksandr, et al.
Published: (2024)
by: Lobanov, Aleksandr, et al.
Published: (2024)
New Aspects of Black Box Conditional Gradient: Variance Reduction and One Point Feedback
by: Veprikov, Andrey, et al.
Published: (2024)
by: Veprikov, Andrey, et al.
Published: (2024)
Accelerated Stochastic ExtraGradient: Mixing Hessian and Gradient Similarity to Reduce Communication in Distributed and Federated Learning
by: Bylinkin, Dmitry, et al.
Published: (2024)
by: Bylinkin, Dmitry, et al.
Published: (2024)
First Order Methods with Markovian Noise: from Acceleration to Variational Inequalities
by: Beznosikov, Aleksandr, et al.
Published: (2023)
by: Beznosikov, Aleksandr, et al.
Published: (2023)
Random-reshuffled SARAH does not need a full gradient computations
by: Beznosikov, Aleksandr, et al.
Published: (2021)
by: Beznosikov, Aleksandr, et al.
Published: (2021)
Decentralized Distributed Optimization for Saddle Point Problems
by: Rogozin, Alexander, et al.
Published: (2021)
by: Rogozin, Alexander, et al.
Published: (2021)
Ito Diffusion Approximation of Universal Ito Chains for Sampling, Optimization and Boosting
by: Ustimenko, Aleksei, et al.
Published: (2023)
by: Ustimenko, Aleksei, et al.
Published: (2023)
Effective Method with Compression for Distributed and Federated Cocoercive Variational Inequalities
by: Medyakov, Daniil, et al.
Published: (2024)
by: Medyakov, Daniil, et al.
Published: (2024)
Linear Convergence Rate in Convex Setup is Possible! Gradient Descent Method Variants under $(L_0,L_1)$-Smoothness
by: Lobanov, Aleksandr, et al.
Published: (2024)
by: Lobanov, Aleksandr, et al.
Published: (2024)
Nesterov's method of dichotomy via Order Oracle: The problem of optimizing a two-variable function on a square
by: Chervonenkis, Boris, et al.
Published: (2024)
by: Chervonenkis, Boris, et al.
Published: (2024)
Hierarchical Mixture-of-Experts with Two-Stage Optimization
by: Molodtsov, Gleb, et al.
Published: (2026)
by: Molodtsov, Gleb, et al.
Published: (2026)
Preconditioned Norms: A Unified Framework for Steepest Descent, Quasi-Newton and Adaptive Methods
by: Veprikov, Andrey, et al.
Published: (2025)
by: Veprikov, Andrey, et al.
Published: (2025)
Stochastic Origin Frank-Wolfe for traffic assignment
by: Ignashin, Igor, et al.
Published: (2025)
by: Ignashin, Igor, et al.
Published: (2025)
Similar Items
-
Sarah Frank-Wolfe: Methods for Constrained Optimization with Best Rates and Practical Features
by: Beznosikov, Aleksandr, et al.
Published: (2023) -
Accelerated Stochastic Gradient Method with Applications to Consensus Problem in Markov-Varying Networks
by: Solodkin, Vladimir, et al.
Published: (2024) -
Methods for Optimization Problems with Markovian Stochasticity and Non-Euclidean Geometry
by: Solodkin, Vladimir, et al.
Published: (2024) -
Unified Theory of Adaptive Variance Reduction
by: Shestakov, Aleksandr, et al.
Published: (2025) -
Methods for Solving Variational Inequalities with Markovian Stochasticity
by: Solodkin, Vladimir, et al.
Published: (2024)