SOTAVerified

Distributed Optimization

The goal of Distributed Optimization is to optimize a certain objective defined over millions of billions of data that is distributed over many machines by utilizing the computational power of these machines.

Source: Analysis of Distributed StochasticDual Coordinate Ascent

Papers

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 171–180 of 536 papers

TitleStatusHype
D-SVM over Networked Systems with Non-Ideal Linking Conditions—0
A Survey on Distributed Evolutionary Computation—0
CEC: Crowdsourcing-based Evolutionary Computation for Distributed Optimization—0
Distributed Optimization for Quadratic Cost Functions over Large-Scale Networks with Quantized Communication and Finite-Time Convergence—0
On Degeneracy Issues in Multi-parametric Programming and Critical Region Exploration based Distributed Optimization in Smart Grid Operations—0
When Evolutionary Computation Meets Privacy—0
On the Convergence of Decentralized Federated Learning Under Imperfect Information SharingCode0
Byzantine-Robust Loopless Stochastic Variance-Reduced GradientCode0
Differentially Private Distributed Convex Optimization—0
Multi-Message Shuffled Privacy in Federated Learning—0
Show:102550
← PrevPage 18 of 54Next →

No leaderboard results yet.