21 citations · 33 across the 5 of their papers we have counts for
5 papers
Reduced storage direct tensor ring decomposition for convolutional neural networks compression
Mateusz Gabor, Rafał Zdunek
Convolutional neural networks (CNNs) are among the most widely used machine learning models for computer vision tasks, such as image classification. To improve the efficiency of CN…
Bearing damage detection with orthogonal and non-negative low-rank feature extraction
Mateusz Gabor, Rafal Zdunek, Agnieszka Wylomanska +1
Local damage of bearings can be detected as a weak cyclic and impulsive component in a highly noisy measured signal. A key problem is how to extract the signal of interest (SOI) fr…
Non-negative tensor factorization for vibration-based local damage detection
Mateusz Gabor, Rafal Zdunek, Radoslaw Zimroz +2
In this study, a novel non-negative tensor factorization (NTF)-based method for vibration-based local damage detection in rolling element bearings is proposed. As the diagnostic si…
Non-negative matrix underapproximation as optimal frequency band selector
Mateusz Gabor, Rafal Zdunek, Radoslaw Zimroz +1
Time-frequency representation (TFR) is often used for non-stationary signal analysis. The most intuitive and interpretable TFR is the spectrogram. Recently, a concept of non-negati…
Bi-level algorithm for optimizing hyperparameters in penalized nonnegative matrix factorization
Nicoletta Del Buono, Flavia Esposito, Laura Selicato +1
Learning approaches rely on hyperparameters that impact the algorithm's performance and affect the knowledge extraction process from data. Recently, Nonnegative Matrix Factorizatio…