Linear Tensor Projection Revealing Nonlinearity

no code implementations • 8 Jul 2020 • Koji Maruhashi, Heewon Park, Rui Yamaguchi, Satoru Miyano

We propose a learning method that searches for a subspace that maximizes the prediction accuracy while retaining as much of the original data information as possible, even if the prediction model in the subspace has strong nonlinearity.

Dimensionality Reduction