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Found 6 papers, 2 papers with code
Reduced storage direct tensor ring decomposition for convolutional neural networks compression
The experiments, performed on the CIFAR-10 and ImageNet datasets, clearly demonstrate the efficiency of RSDTR in comparison to other state-of-the-art CNNs compression approaches.
Bearing damage detection with orthogonal and non-negative low-rank feature extraction
Local damage of bearings can be detected as a weak cyclic and impulsive component in a highly noisy measured signal.
Non-negative tensor factorization for vibration-based local damage detection
In this study, a novel non-negative tensor factorization (NTF)-based method for vibration-based local damage detection in rolling element bearings is proposed.
Non-negative matrix underapproximation as optimal frequency band selector
NMF applied to the spectrogram allows one to find an informative frequency band, which could be further used as a filter characteristic.
Positive concave deep equilibrium models
Deep equilibrium (DEQ) models are widely recognized as a memory efficient alternative to standard neural networks, achieving state-of-the-art performance in language modeling and computer vision tasks.
Fixed points of nonnegative neural networks
We use fixed point theory to analyze nonnegative neural networks, which we define as neural networks that map nonnegative vectors to nonnegative vectors.
