in particular in asymmetric cellular morphologies such as pyramidal neurons.#Here, we adopt a different point of view and relate the spiking of neurons to the LFP through efferent synaptic connections and provid
while the method introduced in Rätsch and Warmuth (2005) incorporates estimates of the achievable maximum margin between two classes. In Gao and Koller (2011), a multiclass method based on boosting and the hinge loss is discussed. Applications of the boosting principle are ...
Results: We propose Scuba, a scalable kernel-based method for gene prioritization. It implements a novel multiple kernel learning approach, based on a semi-supervised perspective and on the optimization of the margin distribution. Scuba is optimized to cope with strongly unbalanced settings where ...
...跟踪[132][133], 同时文献[134]提出基于核(Kernel-based)的 Mean Shift 跟踪算法。 ja.scribd.com|基于14个网页 2. 基于核函数的学习方法 又称有监督的学习方法,主要包括两大类:基于特征向量的学习方法(feature-based)和基于核函数的学习方法(kernel-based… ...
A Kernel Based Method for Discovering Market Segments in Beef Meat Jorge Díez1, Juan José del Coz1, Carlos Sañudo2, Pere Albertí3, and Antonio Bahamonde1 1 Artificial Intelligence Center, University of Oviedo at Gijón (Asturias), Spain {jdiez, juanjo, antonio}@aic.uniovi.es www.aic....
However, the performance of a kernel-based method greatly depends on choosing an optimal kernel function, which is extremely challenging due to the difficulty of explicitly accessing the high dimensional space (Abbasnejad, Ramachandram, & Mandava, 2012). The cross-validation method (Stone, 1974) ...
We can, then, easily decompose the problem into two convex subproblems, and solve using a gradient decent method. The first subproblem would consist of solving for f, in which we assume α is fixed. This reduces to a simple SVM optimization with the kernel characterized by the fixed α: ...
Here we present an exome-wide rare genetic variant association study for 30 blood biomarkers in 191,971 individuals in the UK Biobank. We compare gene-based association tests for separate functional variant categories to increase interpretability and ide
Kernel-Based Laplacian Smoothing Method for 3D Mesh Denoising Hicham Badri1, Mohammed El Hassouni1,2, and Driss Aboutajdine1 1 LRIT, Faculty of Science, 2 DESTEC-FLSHR, University Mohammed V -Agdal- Rabat, Morocco {Hichammbadri,Mohamed.Elhassouni}@gmail.com, aboutaj@fsr.ac.ma Abstract. ...
Using the Expectation–Maximization(EM) method (Dempster, Laird, & Rubin, 1977), we design an iterative scheme for marginal likelihood maximization, where the E-step characterizing the EM method makes use of the Gibbs sampler (see also (Casella, 2001)), and the M-step results in a sequence...