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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

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Showing 311–320 of 536 papers

TitleStatusHype
Auction-based and Distributed Optimization Approaches for Scheduling Observations in Satellite Constellations with Exclusive Orbit Portions—0
Assessing the Impacts of Nonideal Communications on Distributed Optimal Power Flow Algorithms—0
Pixel super-resolved lensless on-chip sensor with scattering multiplexing—0
Optimization in Open Networks via Dual Averaging—0
LocalNewton: Reducing Communication Bottleneck for Distributed Learning—0
Innovation Compression for Communication-efficient Distributed Optimization with Linear Convergence—0
Improving the Transient Times for Distributed Stochastic Gradient Methods—0
Distributed Energy Trading Management for Renewable Prosumers with HVAC and Energy Storage—0
Mean Field MARL Based Bandwidth Negotiation Method for Massive Devices Spectrum Sharing—0
Distributed Experiment Design and Control for Multi-agent Systems with Gaussian Processes—0
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