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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 251–260 of 536 papers

TitleStatusHype
Distributed Unmixing of Hyperspectral Data With Sparsity Constraint—0
Distributed Utility Optimization in Vehicular Communication Systems—0
Distributed Very Large Scale Bundle Adjustment by Global Camera Consensus—0
DOPE: Distributed Optimization for Pairwise Energies—0
Adaptive Consensus ADMM for Distributed Optimization—0
Decentralized Stochastic Multi-Player Multi-Armed Walking Bandits—0
Auction-based and Distributed Optimization Approaches for Scheduling Observations in Satellite Constellations with Exclusive Orbit Portions—0
Decentralized Personalized Federated Learning for Min-Max Problems—0
Decentralized Optimization with Distributed Features and Non-Smooth Objective Functions—0
AttentionX: Exploiting Consensus Discrepancy In Attention from A Distributed Optimization Perspective—0
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