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Contrast preserving decolorization based on the weighted normalized L1 norm
Image decolorization is to transform a color image into a grayscale image with the preserved contrast and consistent details. It is an important tool...
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What the Fork? The Impact of Social Norm Violation on User Behavior
Research indicates that exposure to swearing, an experience often perceived as a norm violation may affect individual and group behaviors. To further...
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Fahrplan zur Umstellung auf die neue Norm
Für die neue Fassung der ISO 27001 stellt sich die Frage, wie man die Änderungen in einem existierenden ISMS berücksichtigt und sie möglichst...
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Pruning filters with L1-norm and capped L1-norm for CNN compression
The blistering progress of convolutional neural networks (CNNs) in numerous applications of the real-world usually obstruct by a surge in network...
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NucNormZSL: nuclear norm-based domain adaptation in zero-shot learning
The ability of human beings to recognize novel concepts has attracted significant attention in the research community. Zero-shot learning, also known...
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Learning low-dimensional manifolds under the L0-norm constraint for unsupervised outlier detection
Unsupervised outlier detection without the need for clean data has attracted great attention because it is suitable for real-world problems as a...
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Nonconvex \(\gamma \)-norm and Laplacian scale mixture with salient map for moving object detection
Moving object detection which has attracted wide attention is the critical issue of computer vision. Consequently, the low-rank and sparse...
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Truncated Minimal-Norm Gauss–Newton Method Applied to the Inversion of FDEM Data
Electromagnetic induction techniques are among the most popular methods for non-invasive investigation of the soil. The collection of data is allowed...
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Novel T-norm for Fuzzy-Rough Rule Induction Algorithm and Its Influence
Machine learning algorithms can generate models in a different output form sometimes in a form of graph, time series or if-then rules. If-then rules...
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Upper norm bounds for the inverse of locally doubly strictly diagonally dominant matrices with its applications in linear complementarity problems
In this paper, we present two error bounds for the linear complementarity problems (LCPs) of locally doubly strictly diagonally dominant (LDSDD)...
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Channel estimation of non-orthogonal multiple access systems based on L2-norm extreme learning machine
In this paper, we study non-orthogonal multiple access (NOMA) transmission system which is a promising technology in future 5G mobile communications....
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Approximation Schemes for Packing Problems with \(\ell _p\) -norm Diversity Constraints
We consider the problem of packing a set of items, each of them from a specific category, to obtain a solution set of high total profit, respecting...
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Approximate \(\mathrm {CVP}_{}\) in Time \(2^{0.802 n}\) - Now in Any Norm!
We show that a constant factor approximation of the shortest and closest lattice vector problem in any norm can be computed in time...
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Improving Robustness of Latent Feature Learning Using L1-Norm
In this era of information explosion, big data are generated from various industrial applications [1–4]. Realizing intelligent recommender systems...
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A Novel Regularized Extreme Learning Machine Based on \(L_{1}\)-Norm and \(L_{2}\)-Norm: a Sparsity Solution Alternative to Lasso and Elastic Net
The aim of this study is to present a new regularized extreme learning machine (ELM) algorithm that can perform variable selection based on the...
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Robust Latent Feature Learning based on Smooth L1-norm
In this era of information explosion, big data for various industrial applications are surrounding people [1–5], such as recommendation systems...
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Towards New Types of Weak Bisimulations for Fuzzy Automata Using the Product T-Norm
Weak bisimulations for fuzzy automata (FAs) are a well-known generalization of bisimulations. While they preserve the language equivalence between...
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L1-norm Laplacian support vector machine for data reduction in semi-supervised learning
As a semi-supervised learning method, Laplacian support vector machine (LapSVM) is popular. Unfortunately, the model generated by LapSVM has a poor...
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Estimation of a treatment effect based on a modified covariates method with \(L_0\) norm
In randomized clinical trials, we assumed the situation that the new treatment is not adequate compared to the control treatment as a result....
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On the Performance of Preconditioned Methods to Solve \(L^{p}\) -Norm Phase Unwrap**
In this paper, we analyze and evaluate suitable preconditioning techniques to improve the performance of the...