Supplementary Material: Extrapolation Towards Imaginary 0-Nearest Neighbour and Its Improved Convergence Rate A Related works Györfi (1981) is the first work that proves the convergence rate O (n

Neural Information Processing Systems 

In this section, we describe Nadaraya-Watson (NW) classifier, Local Polynomial (LP) classifier and their convergence rates (Audibert & Tsybakov, 2007). Proof of Corollary 2. Proposition 6 immediately proves the assertion. We basically follow the proof of Chaudhuri & Dasgupta (2014) Theorem 4(b). In Section G.1, we first define symbols In Section G.2, we describe the sketch of the proof and main differences between our proof and that of Section G.3 shows the main body of the Proof, by utilizing several Lemmas listed in A minimum radius whose measure of the ball is larger than t > 0, i.e., r Chaudhuri & Dasgupta (2014) Lemma 21) Then, the assertion is proved. See the following Section G.4 for Lemma 1-7 used in this proof.