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Consistent Online Gaussian Process Regression Without the Sample Complexity Bottleneck
Gaussian processes provide a framework for nonlinear nonparametric Bayesian inference widely applicable across science and engineering.
Adaptive Kernel Learning in Heterogeneous Networks
We consider learning in decentralized heterogeneous networks: agents seek to minimize a convex functional that aggregates data across the network, while only having access to their local data streams.
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