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Found 3 papers, 1 papers with code
Aggregation in the Mirror Space (AIMS): Fast, Accurate Distributed Machine Learning in Military Settings
Distributed machine learning (DML) can be an important capability for modern military to take advantage of data and devices distributed at multiple vantage points to adapt and learn.
PG3: Policy-Guided Planning for Generalized Policy Generation
In this work, we study generalized policy search-based methods with a focus on the score function used to guide the search over policies.
Achieving Efficient Distributed Machine Learning Using a Novel Non-Linear Class of Aggregation Functions
In this paper, we analyze properties of the WPM and rigorously prove convergence properties of our aggregation mechanism.
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