Inkheart SGD and M4 use bidirectional compression to achieve time complexities in distributed SGD that improve with worker count n and surpass prior lower bounds under a necessary structural assumption.
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The paper presents a mechanism-driven distributed optimization method with convergence guarantees that uses shadow pricing and VCG incentives to motivate self-interested participants to collaborate on coupled problems, forming an interdependent closed loop.
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Scalable Distributed Stochastic Optimization via Bidirectional Compression: Beyond Pessimistic Limits
Inkheart SGD and M4 use bidirectional compression to achieve time complexities in distributed SGD that improve with worker count n and surpass prior lower bounds under a necessary structural assumption.
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Harnessing Individual Motivation for Collective Efficiency: A Mechanism-Driven Distributed Optimization Method
The paper presents a mechanism-driven distributed optimization method with convergence guarantees that uses shadow pricing and VCG incentives to motivate self-interested participants to collaborate on coupled problems, forming an interdependent closed loop.