Results 41 to 50 of about 90,827 (166)
IET Radar, Sonar & Navigation, 2017 Microwave radar 3D imaging with high resolution generally requires a great number of samples. The authors aim at accurate reconstruction of microwave radar images while significantly reducing the required number of samples.
He Tian, Daojing Li
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Sparse PCA: Algorithms, Adversarial Perturbations and Certificates [PDF]
2020 IEEE 61st Annual Symposium on Foundations of Computer Science (FOCS), 2020 We study efficient algorithms for Sparse PCA in standard statistical models (spiked covariance in its Wishart form). Our goal is to achieve optimal recovery guarantees while being resilient to small perturbations. Despite a long history of prior works, including explicit studies of perturbation resilience, the best known algorithmic guarantees for ...
Tommaso d'Orsi +3 more
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A Robust and Sparse Process Fault Detection Method Based on RSPCA
IEEE Access, 2019 As a method widely used in fault detection, principal component analysis (PCA) still has challenges in applicability due to its sensitivity to outliers and its difficulty in principal components (PCs) interpretation.
Peng Peng +4 more
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Optimal Sparse Linear Auto-Encoders and Sparse PCA
CoRR, 2015 Principal components analysis (PCA) is the optimal linear auto-encoder of data, and it is often used to construct features. Enforcing sparsity on the principal components can promote better generalization, while improving the interpretability of the features. We study the problem of constructing optimal sparse linear auto-encoders.
Malik Magdon-Ismail, Christos Boutsidis
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Model study of the leather degradation by oxidation and hydrolysis
Heritage Science, 2019 Many objects of culture heritage, comprised of leather, need to receive the right treatment to be restored and to elongate their lifespan. Determination of the degradation degree and even better the type of the degradation is a crucial knowledge for the ...
Gabriela Vyskočilová +4 more
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Class-Specific Sparse Principal Component Analysis for Visual Classification
IEEE Access, 2020 Extensive research has demonstrated that dictionary learning is active in improving the performance of the representation based classification. However, dictionary learning suffers from lacking an effective dictionary structure that can well tradeoff the
Fei Pan +3 more
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Sparse PCA via Bipartite Matchings
CoRR, 2015 We consider the following multi-component sparse PCA problem: given a set of data points, we seek to extract a small number of sparse components with disjoint supports that jointly capture the maximum possible variance. These components can be computed one by one, repeatedly solving the single-component problem and deflating the input data matrix, but ...
Megasthenis Asteris +3 more
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SUPER-RESOLUTION OF HYPERSPECTRAL IMAGES USING COMPRESSIVE SENSING BASED APPROACH [PDF]
ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2012 Over the past decade hyper spectral (HS) image analysis has turned into one of the most powerful and growing technologies in the field of remote sensing.
R. C. Patel, M. V. Joshi
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On the Worst-Case Approximability of Sparse PCA
CoRR, 2015 20 ...
Siu On Chan +2 more
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IEEE Journal of Translational Engineering in Health and Medicine, 2019 Background: EEG signals are extremely complex in comparison to other biomedical signals, thus require an efficient feature selection as well as classification approach. Traditional feature extraction and classification methods require to reshape the data
Imran Razzak +2 more
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