Cover Image

DADA: Dual Averaging with Distance Adaptation

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Moshtaghifar, Mohammad, Rodomanov, Anton, Vankov, Daniil, Stich, Sebastian
Format:	Preprint
Published:	2025
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

Composite Optimization with Error Feedback: the Dual Averaging Approach
by: Gao, Yuan, et al.
Published: (2025)

Non-Convex Federated Optimization under Cost-Aware Client Selection
by: Jiang, Xiaowen, et al.
Published: (2025)

Non-convex Stochastic Composite Optimization with Polyak Momentum
by: Gao, Yuan, et al.
Published: (2024)

Federated Optimization with Doubly Regularized Drift Correction
by: Jiang, Xiaowen, et al.
Published: (2024)

Stabilized Proximal-Point Methods for Federated Optimization
by: Jiang, Xiaowen, et al.
Published: (2024)

Optimizing $(L_0, L_1)$-Smooth Functions by Gradient Methods
by: Vankov, Daniil, et al.
Published: (2024)

Accelerated Distributed Optimization with Compression and Error Feedback
by: Gao, Yuan, et al.
Published: (2025)

Exploiting Similarity for Computation and Communication-Efficient Decentralized Optimization
by: Takezawa, Yuki, et al.
Published: (2025)

Universality of AdaGrad Stepsizes for Stochastic Optimization: Inexact Oracle, Acceleration and Variance Reduction
by: Rodomanov, Anton, et al.
Published: (2024)

Scalable Decentralized Learning with Teleportation
by: Takezawa, Yuki, et al.
Published: (2025)

Efficient Gradient Methods for Distributed Saddle Problems
by: Luo, Ruichen, et al.
Published: (2026)

Locally Adaptive Federated Learning
by: Mukherjee, Sohom, et al.
Published: (2023)

Global Complexity Analysis of BFGS
by: Rodomanov, Anton
Published: (2024)

FedMuon: Federated Learning with Bias-corrected LMO-based Optimization
by: Takezawa, Yuki, et al.
Published: (2025)

Communication-Efficient Gradient Descent-Accent Methods for Distributed Variational Inequalities: Unified Analysis and Local Updates
by: Zhang, Siqi, et al.
Published: (2023)

On Convergence of Incremental Gradient for Non-Convex Smooth Functions
by: Koloskova, Anastasia, et al.
Published: (2023)

Towards Faster Decentralized Stochastic Optimization with Communication Compression
by: Islamov, Rustem, et al.
Published: (2024)

Layer-wise Quantization for Quantized Optimistic Dual Averaging
by: Nguyen, Anh Duc, et al.
Published: (2025)

Adaptive Methods for Variational Inequalities under Relaxed Smoothness Assumption
by: Vankov, Daniil, et al.
Published: (2024)

Last Iterate Convergence of Popov Method for Non-monotone Stochastic Variational Inequalities
by: Vankov, Daniil, et al.
Published: (2023)

Generalized Smooth Stochastic Variational Inequalities: Almost Sure Convergence and Convergence Rates
by: Vankov, Daniil, et al.
Published: (2024)

Stability of the Monge Map in Semi-Dual Optimal Transport
by: Selitskiy, Anton, et al.
Published: (2026)

Regularized Adaptive Momentum Dual Averaging with an Efficient Inexact Subproblem Solver for Training Structured Neural Network
by: Huang, Zih-Syuan, et al.
Published: (2024)

Revisiting LocalSGD and SCAFFOLD: Improved Rates and Missing Analysis
by: Luo, Ruichen, et al.
Published: (2025)

Robust Regression over Averaged Uncertainty
by: Bertsimas, Dimitris, et al.
Published: (2023)

Fast Minimization of Expected Logarithmic Loss via Stochastic Dual Averaging
by: Tsai, Chung-En, et al.
Published: (2023)

Constrained Sampling with Primal-Dual Langevin Monte Carlo
by: Chamon, Luiz F. O., et al.
Published: (2024)

Planning and Learning in Average Risk-aware MDPs
by: Wang, Weikai, et al.
Published: (2025)

Regularized Q-learning through Robust Averaging
by: Schmitt-Förster, Peter, et al.
Published: (2024)

A Unified Analysis for Finite Weight Averaging
by: Wang, Peng, et al.
Published: (2024)

Optimal Data Splitting in Distributed Optimization for Machine Learning
by: Medyakov, Daniil, et al.
Published: (2024)

The Ky Fan Norms and Beyond: Dual Norms and Combinations for Matrix Optimization
by: Kravatskiy, Alexey, et al.
Published: (2025)

Central Limit Theorems for Asynchronous Averaged Q-Learning
by: Liu, Xingtu
Published: (2025)

Refined Analysis of Federated Averaging and Federated Richardson-Romberg
by: Mangold, Paul, et al.
Published: (2024)

A Simplified Analysis of SGD for Linear Regression with Weight Averaging
by: Meterez, Alexandru, et al.
Published: (2025)

Sample Complexity of Distributionally Robust Average-Reward Reinforcement Learning
by: Chen, Zijun, et al.
Published: (2025)

Unified Convergence Analysis for Adaptive Optimization with Moving Average Estimator
by: Guo, Zhishuai, et al.
Published: (2021)

Performance of NPG in Countable State-Space Average-Cost RL
by: Murthy, Yashaswini, et al.
Published: (2024)

Optimal Sample Complexity for Average Reward Markov Decision Processes
by: Wang, Shengbo, et al.
Published: (2023)

A Dual Basis Approach for Structured Robust Euclidean Distance Geometry
by: Kundu, Chandra, et al.
Published: (2025)