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stat.ML2024
Aggregation Models with Optimal Weights for Distributed Gaussian Processes
Haoyuan Chen, Rui Tuo
Gaussian process (GP) models have received increasing attention in recent years due to their superb prediction accuracy and modeling flexibility. To address the computational burde…
stat.ML2024
Beyond State Space Representation: A General Theory for Kernel Packets
Liang Ding, Rui Tuo, Lu Zhou
Gaussian process (GP) regression provides a flexible, nonparametric framework for probabilistic modeling, yet remains computationally demanding in large-scale applications. For one…