3. Revisiting Normalization
3.1 Revisiting Euclidean Normalization
4 Riemannian Normalization on Lie Groups
5 LieBN on the Lie Groups of SPD Manifolds and 5.1 Deformed Lie Groups of SPD Manifolds
7 Conclusions, Acknowledgments, and References
APPENDIX CONTENTS
B Basic layes in SPDnet and TSMNet
C Statistical Results of Scaling in the LieBN
D LieBN as a Natural Generalization of Euclidean BN
E Domain-specific Momentum LieBN for EEG Classification
F Backpropagation of Matrix Functions
G Additional Details and Experiments of LieBN on SPD manifolds
H Preliminary Experiments on Rotation Matrices
I Proofs of the Lemmas and Theories in the Main Paper
Now, we showcase our LieBN framework illustrated in Alg. 1 on SPD manifolds. As discussed in Sec. 5.1, there are three families of left-invariant metrics, namely (θ, α, β)-AIM, (α, β)-LEM, and θ-LCM. Since all three metric families are pullback metrics, the LieBN based on these metrics can be simplified and calculated in the co-domain. We denote Alg. 1 as
Then we can obtain the following theorem.
This paper is available on arxiv under CC BY-NC-SA 4.0 DEED license.
Authors:
(1) Ziheng Chen, University of Trento;
(2) Yue Song, University of Trento and a Corresponding author;
(3) Yunmei Liu, University of Louisville;
(4) Nicu Sebe, University of Trento.