Robust and sparse multigroup classification by the optimal scoring approach
Sign Up to like & getrecommendations! Published in 2020 at "Data Mining and Knowledge Discovery"
DOI: 10.1007/s10618-019-00666-8
Abstract: We propose a robust and sparse classification method based on the optimal scoring approach. It is also applicable if the number of variables exceeds the number of observations. The data are first projected into a… read more here.
Keywords: robust sparse; classification; optimal scoring; classification optimal ... See more keywords
Learning double weights via data augmentation for robust sparse and collaborative representation-based classification
Sign Up to like & getrecommendations! Published in 2020 at "Multimedia Tools and Applications"
DOI: 10.1007/s11042-020-08918-2
Abstract: Image classification is a hot technique applied in many multimedia systems, where both l 1 and l 2 regularizations have shown potential for robust sparse representation-based image classification. However, previous studies showed that l 1… read more here.
Keywords: robust sparse; classification; double weights; data augmentation ... See more keywords
MoG-Based Robust Sparse Representation for Seismic Erratic Noise Suppression
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Geoscience and Remote Sensing Letters"
DOI: 10.1109/lgrs.2020.3022985
Abstract: By modeling the noise as Gaussian distribution, quite a lot of methods, such as basis pursuit denoising (BPDN), have demonstrated their great effectiveness in suppressing commonly random seismic noise. However, when it comes to complex… read more here.
Keywords: noise; sparse representation; robust sparse; distribution ... See more keywords
Robust Sparse Recovery in Impulsive Noise via Continuous Mixed Norm
Sign Up to like & getrecommendations! Published in 2018 at "IEEE Signal Processing Letters"
DOI: 10.1109/lsp.2018.2846479
Abstract: This letter investigates the problem of sparse signal recovery in the presence of additive impulsive noise. The heavy-tailed impulsive noise is well modeled with stable distributions. Since there is no explicit formula for the probability… read more here.
Keywords: recovery; robust sparse; formula; impulsive noise ... See more keywords
The Robust Sparse Fourier Transform (RSFT) and Its Application in Radar Signal Processing
Sign Up to like & getrecommendations! Published in 2017 at "IEEE Transactions on Aerospace and Electronic Systems"
DOI: 10.1109/taes.2017.2714918
Abstract: The Sparse Fourier Transform (SFT), designed for signals that contain a small number of frequencies, enjoys low complexity, and thus is ideally suited for big data applications. In this paper, we propose Robust Sparse Fourier… read more here.
Keywords: robust sparse; transform rsft; rsft; fourier transform ... See more keywords
Weakly Convex Regularized Robust Sparse Recovery Methods With Theoretical Guarantees
Sign Up to like & getrecommendations! Published in 2019 at "IEEE Transactions on Signal Processing"
DOI: 10.1109/tsp.2019.2935906
Abstract: Robust sparse signal recovery against impulsive noise is a core issue in many applications. Numerous methods have been proposed to recover the sparse signal from measurements corrupted by various impulsive noises, but most of them… read more here.
Keywords: sparse signal; weakly convex; recovery; robust sparse ... See more keywords
Robust and sparse portfolio model for index tracking
Sign Up to like & getrecommendations! Published in 2018 at "Journal of Industrial and Management Optimization"
DOI: 10.3934/jimo.2018082
Abstract: In the context of index tracking, the tracking error measures the difference between the return an investor receives and that of the benchmark he was attempting to imitate. In this paper, we use the weighted… read more here.
Keywords: robust sparse; index; portfolio model; sparse portfolio ... See more keywords