Methods › General › Replicated Data Parallel › DABMD
Distributed Any-Batch Mirror Descent
DABMD
archive 2025-07-28 Description, source and code snippet are the archive's method entry.
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 archive 2025-07-28
1 shown of 1, newest first. Repository counts are the archive's code-links table. A Syntology line states what Syntology ran from that paper's harvested code; it is per sample and not a correctness claim.
-
Distributed Online Optimization over a Heterogeneous Network 1 Jan 2020 · 0 repositories
Tasks archive 2025-07-28
The archive attaches no task to a paper tagged with this method.
Usage over time archive 2025-07-28
Components: the archive holds no method-to-method composition, so PwC's Components table cannot be rebuilt; the Papers list carries no Results column for the same reason (the archive does not join its leaderboard rows to method tags).
Categories archive 2025-07-28
Report a problem or propose a change · a person checks every report against the paper or source before anything changes; decisions are listed on /corrections