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
Distributed Averaging Methods for Randomized Second Order Optimization—0
Distributed Collision-Free Motion Coordination on a Sphere: A Conic Control Barrier Function Approach—0
Distributed Convex Optimization With Limited Communications—0
Distributed Convex Optimization with State-Dependent (Social) Interactions over Random Networks—0
Distributed Coordination of Multi-Microgrids in Active Distribution Networks for Provisioning Ancillary Services—0
Distributed CPU Scheduling Subject to Nonlinear Constraints—0
Correlated Quantization for Faster Nonconvex Distributed Optimization—0
Distributed Delay-Tolerant Strategies for Equality-Constraint Sum-Preserving Resource Allocation—0
Distributed Difference of Convex Optimization—0
Correlated quantization for distributed mean estimation and optimization—0
Show:102550
← PrevPage 18 of 54Next →

No leaderboard results yet.