Polynomial Regression on Riemannian Manifolds
Polynomial Regression on Riemannian Manifolds
Polynomial Regression on Riemannian Manifolds
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N∑<br />
((DΓ(u, v))w)i = (wi − wj) T (ui − uj)γ ′ (|xi − xj| 2 )(K −1 v)j<br />
j=1<br />
N∑<br />
+ 2 (xi − xj) T (ui − uj)(xi − xj) T (wi − wj)γ ′′ (|xi − xj| 2 )(K −1 v)j<br />
j=1<br />
N∑<br />
+ (xi − xj) T (ui − uj)γ ′ (|xi − xj| 2 )(( d dɛ K−1 )v)j<br />
j=1<br />
N∑<br />
+ (wi − wj) T (vi − vj)γ ′ (|xi − xj| 2 )(K −1 u)j<br />
j=1<br />
N∑<br />
+ 2 (xi − xj) T (vi − vj)(xi − xj) T (wi − wj)γ ′′ (|xi − xj| 2 )(K −1 u)j<br />
j=1<br />
N∑<br />
+ (xi − xj) T (vi − vj)γ ′ (|xi − xj| 2 )(( d dɛ K−1 )u)j<br />
j=1<br />
N∑<br />
N∑<br />
− 2 (xi − xj) T (wi − wj)γ ′ (|xi − xj| 2 ) (xj − xk)γ ′ (|xj − xk| 2 )((K −1 u) T k (K−1 v)j + (K −1 u) T j (K −1 v)k)<br />
j=1<br />
k=1<br />
N∑<br />
N∑<br />
− γ(|xi − xj| 2 ) (wj − wk)γ ′ (|xj − xk| 2 )((K −1 u) T k (K−1 v)j + (K −1 u) T j (K −1 v)k)<br />
j=1<br />
k=1<br />
N∑<br />
N∑<br />
− 2 γ(|xi − xj| 2 ) (xj − xk)(xj − xk) T (wj − wk)γ ′′ (|xj − xk| 2 )((K −1 u) T k (K−1 v)j + (K −1 u) T j (K −1 v)k)<br />
j=1<br />
k=1<br />
N∑<br />
N∑<br />
− γ(|xi − xj| 2 ) (xj − xk)γ ′ (|xj − xk| 2 )<br />
j=1<br />
k=1<br />
× (( d dɛ K−1 u) T k (K−1 v)j + (K −1 u) T k ( d dɛ K−1 v)j + ( d dɛ K−1 u) T j (K −1 v)k + (K −1 u) T j ( d dɛ K−1 v)k)<br />
(<br />
( d )<br />
dɛ K−1 )v = −(K −1 d<br />
i dɛ KK−1 v)i<br />
∑ N<br />
= −2(K −1 (xk − xj) T (wk − wj)γ ′ (|xk − xj| 2 )(K −1 v)j<br />
j=1<br />
<str<strong>on</strong>g>Polynomial</str<strong>on</strong>g> <str<strong>on</strong>g>Regressi<strong>on</strong></str<strong>on</strong>g> <strong>on</strong> <strong>Riemannian</strong> <strong>Manifolds</strong> 30