Streaming kernel regression with provably adaptive mean, variance, and regularization

We consider the problem of streaming kernel regression, when the observations arrive sequentially and the goal is to recover the underlying mean function, assumed to belong to an RKHS. The variance of the noise is not assumed to be known... (read more)

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