Results 241 to 250 of about 300,398 (297)

Construction of a nomogram combining CT and serum markers for predicting macrolide resistance gene mutation status in pediatric Mycoplasma pneumoniae pneumonia. [PDF]

Front Pediatr
Yuan X, Xin R, Wang L, Ling J, Li Y, Pang L.   +5 more
europepmc   +1 more source

Lp-norm estimation for nonlinear regression models

, 1997
openaire   +2 more sources

lp-Norm Multiple Kernel Learning

J. Mach. Learn. Res., 2011
Ziel des Maschinellen Lernens ist das Erlernen unbekannter Konzepte aus Daten. In vielen aktuellen Anwendungsbereichen des Maschinellen Lernens, wie zum Beispiel der Bioinformatik oder der Computer Vision, sind die Daten auf vielfältige Art und Weise in Merkmalsgruppierungen repräsentiert.
Marius Kloft, Ulf Brefeld, Sören Sonnenburg, Alexander Zien   +3 more
core   +6 more sources

Asymptotic Performance of Lp-Norm MIMO Detection

2010 IEEE 72nd Vehicular Technology Conference - Fall, 2010
Full search L1-norm (FS-L1) and sphere decoding Linfty-norm (SD-Linfty) detectors have been previously proposed for multiple-input multiple-output (MIMO) systems as they entail a lower receiver complexity than the optimal L2-norm detector. However, the performance loss caused by application of these suboptimal detectors in additive white Gaussian noise
Imtiaz Ahmed 0001, Robert Schober, Ranjan K. Mallik   +2 more
openaire   +2 more sources

Lp-Norm IDF for Large Scale Image Search

2013 IEEE Conference on Computer Vision and Pattern Recognition, 2013
The Inverse Document Frequency (IDF) is prevalently utilized in the Bag-of-Words based image search. The basic idea is to assign less weight to terms with high frequency, and vice versa. However, the estimation of visual word frequency is coarse and heuristic.
Liang Zheng 0001, Shengjin Wang, Ziqiong Liu, Qi Tian 0001   +3 more
openaire   +2 more sources

Efficient and Accurate Lp-Norm Multiple Kernel Learning.

, 2010
Learning 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, Brefeld, U., Sonnenburg, S., Laskov, P., Müller, K., Zien, A.   +5 more
openaire   +3 more sources

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Oblivious Routing for the Lp-norm

2009 50th Annual IEEE Symposium on Foundations of Computer Science, 2009
Gupta et al. [GHR06] introduced a very general multi-commodity flow problem in which the cost of a given flow solution on a graph G=(V, E) is calculated by first computing the link loads via a load-function l, that describes the load of a link as a function of the flow traversing the link, and then aggregating the individual link loads into a single ...
Matthias Englert, Harald Räcke
openaire   +1 more source

Least Lp-norm low-pass filter

Automatica, 2021
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
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Partitioning under the Lp norm

European Journal of Operational Research, 2000
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Robert R. Goldberg, Jacob Shapiro
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Independent component analysis by lp-norm optimization

Pattern Recognition, 2018
Abstract In this paper, a couple of new algorithms for independent component analysis (ICA) are proposed. In the proposed methods, the independent sources are assumed to follow a predefined distribution of the form f ( s ) = α exp ( − β | s | p ) and a maximum likelihood estimation is used to separate the sources.
Sungheon Park, Nojun Kwak
openaire   +1 more source