This paper considers a series estimator of 𝗕E[α(Y) λ(X) = λ̄], (α,λ) ∈ 𝒜 × Λ, indexed by function spaces, and establishes the estimator's uniform convergence rate over λ̄ ∈ R, α ∈ 𝐑, and λ ∈ Λ, ...
This is a preview. Log in through your library . Abstract In the present paper, we shall establish one of our earlier conjectures by proving that on compact subsets of a *-foundation semigroup S with ...
Abstract: In many practical learning problems, training samples are not i.i.d., and there is an intrinsic dependency among samples. Therefore, theoretical study of learning with dependent data has ...
Abstract: We consider deep neural networks (DNNs) with a Lipschitz continuous activation function and with weight matrices of variable widths. We establish a uniform convergence analysis framework in ...