Appendix Fugue: Slow-Worker-Agnostic Distributed Learning for Big Models on Big Data
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Table 1: Final tuned parameter values for Fugue, BarrieredFugue, GraphLab and PSGD. All the methods are tuned to perform optimally. η0 is the initial step size, where η is defined in equation 4. λ is the Dictionary Learning `1 penalty defined in equation 2. η ′ is parameter that modifies the learning rate when extra updates are executed while waiting for slow workers. step dec is a parameter for decreasing learning rate for GraphLab used in their collaborative filtering library.
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تاریخ انتشار 2014