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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 71–80 of 536 papers

TitleStatusHype
Cooperative Integrated Sensing and Communication Networks: Analysis and Distributed Design—0
Communication- and Computation-Efficient Distributed Submodular Optimization in Robot Mesh NetworksCode0
Provable Privacy Advantages of Decentralized Federated Learning via Distributed Optimization—0
Fast Distributed Optimization over Directed Graphs under Malicious Attacks using Trust—0
Graphon Particle Systems, Part II: Dynamics of Distributed Stochastic Continuum Optimization—0
Accelerating Distributed Optimization: A Primal-Dual Perspective on Local Steps—0
Graph Neural Networks Gone Hogwild—0
Distributed Utility Optimization in Vehicular Communication Systems—0
A KL-based Analysis Framework with Applications to Non-Descent Optimization Methods—0
ACCO: Accumulate While You Communicate for Communication-Overlapped Sharded LLM TrainingCode1
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