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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 151–160 of 536 papers

TitleStatusHype
EControl: Fast Distributed Optimization with Compression and Error Control—0
Zeroth-Order Feedback-Based Optimization for Distributed Demand Response—0
Correlation Aware Sparsified Mean Estimation Using Random Projection—0
Machine Learning Infused Distributed Optimization for Coordinating Virtual Power Plant Assets—0
Distributed Delay-Tolerant Strategies for Equality-Constraint Sum-Preserving Resource Allocation—0
Distributed Linear Regression with Compositional Covariates—0
Distributed Continuous-Time Optimization with Uncertain Time-Varying Quadratic Cost Functions—0
Detecting Shared Data Manipulation in Distributed Optimization Algorithms—0
LASER: Linear Compression in Wireless Distributed Optimization—0
Network-aware EV charging and discharging in unbalanced distribution grids: A distributed, robust approach against communication failures—0
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