Nov 15, 2020 · In this paper, we develop an interpretable dimension reduction approach called Regularized Higher Order Principal Components Analysis.

In this paper, we develop an interpretable dimension reduction approach called Regularized Higher Order Principal Components Analysis, as well as an extension ...

In this paper, we develop an interpretable dimension reduction approach called Regularized Higher Order Principal Components. Analysis, as well as an extension ...

In this paper, we develop an interpretable dimension reduction approach called Regularized Higher Order Principal Components Analysis.

Nov 15, 2020 · In this paper, we develop an interpretable dimension reduction approach called Regularized Higher Order Principal Components. Analysis, as well ...

In this paper, we develop an interpretable dimension reduction approach called Regularized Higher Order Principal Components Analysis, as well as an extension ...

In order to adapt our approach to the many-graph setting (as opposed to two graphs), it is necessary to use a multiple PLS or multiple CCA approach, ...

Interpretable Visualization and Higher-Order Dimension Reduction for ECoG Data ... After signal processing, this type of data may be organized as a 4-way tensor ...

Dimension reduction techniques are used for visualizing, exploring, and discovering patterns in large data sets. We have developed many dimension reduction ...

Interpretable visualization and higher-order dimension reduction for ECoG data. K Geyer, F Campbell, A Chang, J Magnotti, M Beauchamp, GI Allen. 2020 IEEE ...