17 citations · 70 across the 21 of their papers we have counts for
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cs.LG2020
Boosting First-Order Methods by Shifting Objective: New Schemes with Faster Worst-Case Rates
Kaiwen Zhou, Anthony Man-Cho So, James Cheng
We propose a new methodology to design first-order methods for unconstrained strongly convex problems. Specifically, instead of tackling the original objective directly, we constru…
cs.LG2019
Voting-Based Multi-Agent Reinforcement Learning for Intelligent IoT
Yue Xu, Zengde Deng, Mengdi Wang +3
The recent success of single-agent reinforcement learning (RL) in Internet of things (IoT) systems motivates the study of multi-agent reinforcement learning (MARL), which is more c…