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Register a new userGraph Oracle Models, Lower Bounds, and Gaps for Parallel Stochastic Optimization
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Added by
Blake Woodworth
Publication date
2018
fields
Informatics Engineering
and research's language is
English
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We suggest a general oracle-based framework that captures different parallel stochastic optimization settings described by a dependency graph, and derive generic lower bounds in terms of this graph. We then use the framework and derive lower bounds for several specific parallel optimization settings, including delayed updates and parallel processing with intermittent communication. We highlight gaps between lower and upper bounds on the oracle complexity, and cases where the natural algorithms are not known to be optimal.
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