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Robust and sparse tensor analysis with Lp-norm maximization
2017 8th IEEE International Conference on Software Engineering and Service Science (ICSESS), 2017Tensor PCA, which can make full use of the spatial relationship of images/videos, plays an important role in computer vision and image analysis. The proposed method is robust to outliers because of using the adjustable Lp-norm. The elastic net, which generalizes the sparsity-inducing lasso penalty by combining the ridge penalty, is integrated into the ...
Ganyi Tang, Guifu Lu, Zhongqun Wang
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Fast Time Sequence Indexing for Arbitrary Lp Norms
2007Fast indexing in time sequence databases for similarity searching has attracted a lot of research recently. Most of the proposals, however, typically centered around the Euclidean distance and its derivatives. We examine the problem of multimodal similarity search in which users can choose the best one from multiple similarity models for their needs.
Byoung-Kee Yi, Faloutsos, Christos
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ISS in Spatial Lp Norms for Hyperbolic PDEs
2018The chapter deals with the derivation of ISS estimates expressed in spatial \( L^{p} \) norms for 1-D, first-order, hyperbolic PDEs with a constant transport velocity. Two different methodologies for deriving ISS estimates are provided. The first methodology is the use of ISS-Lyapunov Functionals (ISS-LFs).
Iasson Karafyllis, Miroslav Krstic
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Efficient and Accurate Lp-Norm Multiple Kernel Learning
2010Learning linear combinations of multiple kernels is an appealing strategy when the right choice of features is unknown. Previous approaches to multiple kernel learning (MKL) promote sparse kernel combinations and hence support interpretability. Unfortunately, L1-norm MKL is hardly observed to outperform trivial baselines in practical applications.
Kloft, M. ; https://orcid.org/0000-0001-6829-3725 +5 more
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Tensor Robust Principal Component Analysis with a New Tensor Nuclear Norm
IEEE Transactions on Pattern Analysis and Machine Intelligence, 2020Canyi Lu, Jiashi Feng, Yudong Chen
exaly
Laplacian Lp norm least squares twin support vector machine
Pattern Recognition, 2023Xijiong Xie +6 more
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