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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 221–230 of 536 papers

TitleStatusHype
A Mirror Descent-Based Algorithm for Corruption-Tolerant Distributed Gradient Descent—0
Distributed Optimization for Traffic Light Control and Connected Automated Vehicle Coordination in Mixed-Traffic Intersections—0
Deep Learning for Distributed Optimization: Applications to Wireless Resource Management—0
Distributed optimization in wireless sensor networks: an island-model framework—0
Distributed Optimization of Convex Sum of Non-Convex Functions—0
Distributed Optimization of Graph Convolutional Network using Subgraph Variance—0
Deep Distributed Optimization for Large-Scale Quadratic Programming—0
Distributed Optimization Strategy for Multi Area Economic Dispatch Based on Electro Search Optimization Algorithm—0
DEED: A General Quantization Scheme for Communication Efficiency in Bits—0
Information-Geometric Barycenters for Bayesian Federated Learning—0
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