125 citations · 230 across the 10 of their papers we have counts for
5 papers · 1 filter
Prototype-Rule Neurosymbolic Regularization for Rank-Constrained Tensor Neural Networks under Label Scarcity
Eftychios Protopapadakis, Konstantinos Makantasis, Konstantinos M. Giannoutakis
Rank-constrained tensor neural networks reduce the parameterization of high-order inputs, but they do not explicitly constrain class geometry in the learned representation. This st…
Rank-R FNN: A Tensor-Based Learning Model for High-Order Data Classification
Konstantinos Makantasis, Alexandros Georgogiannis, Athanasios Voulodimos +3
An increasing number of emerging applications in data science and engineering are based on multidimensional and structurally rich data. The irregularities, however, of high-dimensi…
Space-Time Domain Tensor Neural Networks: An Application on Human Pose Classification
Konstantinos Makantasis, Athanasios Voulodimos, Anastasios Doulamis +2
Recent advances in sensing technologies require the design and development of pattern recognition models capable of processing spatiotemporal data efficiently. In this study, we pr…
Common Mode Patterns for Supervised Tensor Subspace Learning
Konstantinos Makantasis, Anastasios Doulamis, Nikolaos Doulamis +1
In 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 conside…
Tensor-based Nonlinear Classifier for High-Order Data Analysis
Konstantinos Makantasis, Anastasios Doulamis, Nikolaos Doulamis +2
In this paper we propose a tensor-based nonlinear model for high-order data classification. The advantages of the proposed scheme are that (i) it significantly reduces the number o…