A Simple Parallel Algorithm with an $O(1/t)$ Convergence Rate for General Convex Programs
From MaRDI portal
Publication:5737727
DOI10.1137/16M1059011zbMath1365.90207arXiv1512.08370OpenAlexW2963576077MaRDI QIDQ5737727
No author found.
Publication date: 30 May 2017
Published in: SIAM Journal on Optimization (Search for Journal in Brave)
Full work available at URL: https://arxiv.org/abs/1512.08370
Related Items (5)
Complexity of an inexact proximal-point penalty method for constrained smooth non-convex optimization ⋮ A Low Complexity Algorithm with $O(\sqrt{T})$ Regret and $O(1)$ Constraint Violations for Online Convex Optimization with Long Term Constraints ⋮ A Privacy-Preserving Method to Optimize Distributed Resource Allocation ⋮ Iteration complexity of inexact augmented Lagrangian methods for constrained convex programming ⋮ Decentralized hierarchical constrained convex optimization
Cites Work
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Distributed Optimization and Statistical Learning via the Alternating Direction Method of Multipliers
- On the sublinear convergence rate of multi-block ADMM
- Subgradient methods for saddle-point problems
- Introductory lectures on convex optimization. A basic course.
- Stochastic Network Optimization with Application to Communication and Queueing Systems
- On the $O(1/n)$ Convergence Rate of the Douglas–Rachford Alternating Direction Method
- Rate Analysis of Inexact Dual First-Order Methods Application to Dual Decomposition
- Rate control for communication networks: shadow prices, proportional fairness and stability
- Approximate Primal Solutions and Rate Analysis for Dual Subgradient Methods
- A Distributed Newton Method for Network Utility Maximization–I: Algorithm
- An <formula formulatype="inline"><tex Notation="TeX">$O(1/k)$</tex> </formula> Gradient Method for Network Resource Allocation Problems
- Nonlinear Programming
This page was built for publication: A Simple Parallel Algorithm with an $O(1/t)$ Convergence Rate for General Convex Programs
