Communication-aware Distributed Gaussian Process Regression Algorithms for Real-time Machine Learning
Abstract: 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.
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