Communication-aware Distributed Gaussian Process Regression Algorithms for Real-time Machine Learning
Communication-aware Distributed Gaussian Process Regression Algorithms for Real-time Machine Learning
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DOI：
10.23919/acc45564.2020.9147886
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发表时间：
2020-07
期刊：
影响因子：
--
通讯作者：
Zhenyuan Yuan;Minghui Zhu
中科院分区：
文献类型：
--
作者：
Zhenyuan Yuan;Minghui Zhu
我们提出了一种通信感知的高斯过程回归算法，该算法允许机器人网络使用流数据在真实的时间内协作学习共同的潜在函数。我们量化的改善，机器人间的通信带来的学习算法的瞬态性能。仿真结果验证了该算法的有效性。
We propose a communication-aware Gaussian process regression algorithm that allows a network of robots to collaboratively learn about a common latent function in real time using streaming data. We quantify the improvement that inter-robot communication brings on the transient performance of the learning algorithm. Simulations are performed to validate the proposed algorithm.