Distributed Methods
Distributed Any-Batch Mirror Descent
Distributed Any-Batch Mirror Descent (DABMD) is based on distributed Mirror Descent but uses a fixed per-round computing time to limit the waiting by fast nodes to receive information updates from slow nodes. DABMD is characterized by varying minibatch sizes across nodes. It is applicable to a broader range of problems compared with existing distributed online optimization methods such as those based on dual averaging, and it accommodates time-varying network topology.
Papers
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Usage Over Time
Components
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| 🤖 No Components Found | You can add them if they exist; e.g. Mask R-CNN uses RoIAlign |
