2 citations · 3 across the 3 of their papers we have counts for
3 papers
cs.LG2022
Aggregation in the Mirror Space (AIMS): Fast, Accurate Distributed Machine Learning in Military Settings
Ryan Yang, Haizhou Du, Andre Wibisono +1
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 lear…
cs.AI2022★ 2 cited
PG3: Policy-Guided Planning for Generalized Policy Generation
Ryan Yang, Tom Silver, Aidan Curtis +2
A longstanding objective in classical planning is to synthesize policies that generalize across multiple problems from the same domain. In this work, we study generalized policy se…
cs.LG2022★ 1 cited
Achieving Efficient Distributed Machine Learning Using a Novel Non-Linear Class of Aggregation Functions
Haizhou Du, Ryan Yang, Yijian Chen +3
Distributed machine learning (DML) over time-varying networks can be an enabler for emerging decentralized ML applications such as autonomous driving and drone fleeting. However, t…