Supplementary Material: Experimental Design for Linear Functionals in Reproducing Kernel Hilbert Spaces A Estimability results

In A.1, we show consequence of Def. 1 which is used in the proofs We can apply Theorem??, to get C We show that our condition in Def. 1 and Pukelsheims and estimability This definition is sometimes used as restatement of the estimability property. Definition 4 (Projected data) . Lemma 2. The assumption in Definition 4 implies the assumption in Definition 1 with This section includes proofs for the concentration results presented in the main text. Z is as in Def. 2 where X The term above is so called self-normalized noise, which can be handled by techniques of de la Peña et al. (2009) popularized by Abbasi-Y adkori et al. (2011). From now on the proof is generic.