Results 201 to 210 of about 5,042 (258)
Linear reflected backward stochastic differential equations arising from vulnerable claims in markets with random horizon. [PDF]
Choulli T, Alsheyab S.
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Predictability of a Mandibular Corpus Length Multivariate Model Integrating Björk-Jarabak Measurements and the Cephalometric Norm. [PDF]
Balderas-González ME +9 more
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Graph transformer for link prediction on N-ary facts. [PDF]
Hu B, Tao X, Guo H, Li J, Pang G, Xie D.
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Autoregressive model in the Lp norm space for EEG analysis
Journal of Neuroscience Methods, 2015The autoregressive (AR) model is widely used in electroencephalogram (EEG) analyses such as waveform fitting, spectrum estimation, and system identification. In real applications, EEGs are inevitably contaminated with unexpected outlier artifacts, and this must be overcome.
Fali Li, Peiyang Li, Yin Tian
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lp-Norm Multiple Kernel Learning
J. Mach. Learn. Res., 2011Ziel 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 +3 more
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Oblivious Routing for the Lp-norm
2009 50th Annual IEEE Symposium on Foundations of Computer Science, 2009Gupta 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
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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, 2000zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Robert R. Goldberg, Jacob Shapiro
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Asymptotic Performance of Lp-Norm MIMO Detection
2010 IEEE 72nd Vehicular Technology Conference - Fall, 2010Full 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 +2 more
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