Common mode patterns for supervised tensor subspace learningCommon mode patterns for supervised tensor subspace learning Πλήρης Δημοσίευση σε Συνέδριο Conference Full Paper 2020-06-152019enIn this work we propose a method for reducing the dimensionality of tensor objects in a binary classification framework. The proposed Common Mode Patterns method takes into consideration the labels' information, and ensures that tensor objects that belong to different classes do not share common features after the reduction of their dimensionality. We experimentally validate the proposed supervised subspace learning technique and compared it against Multilinear Principal Component Analysis using a publicly available hyper-spectral imaging dataset. Experimental results indicate that the proposed CMP method can efficiently reduce the dimensionality of tensor objects, while, at the same time, increasing the inter-class separability.http://creativecommons.org/licenses/by/4.0/2927-293144th IEEE International Conference on Acoustics, Speech, and Signal Processing Makantasis Konstantinos Μακαντασης Κωνσταντινος Doulamis, Anastasios Doulamis Nikolaos D. Voulodimos, Athanasios Institute of Electrical and Electronics Engineers Common mode patterns Supervised tensor subspace learning Tensor dimensionality reduction