Partial Least Square Regression via Three-factor SVD-type Manifold Optimization for EEG Decoding. (arXiv:2208.04324v2 [cs.LG] UPDATED)

Partial least square regression (PLSR) is a widely-used statistical model to
reveal the linear relationships of latent factors that comes from the
independent variables and dependent variables. However, traditional methods to
solve PLSR models are usually based on the Euclidean space, and easily getting
stuck into a local minimum. To this end, we propose a new method to solve the
partial least square regression, named PLSR via optimization on bi-Grassmann
manifold (PLSRbiGr). Specifically, we first leverage the three-factor SVD-type
decomposition …

arxiv least lg manifold optimization regression svd type