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 ...
the Gaussian kernel-based method was employed to output two similarity matrixes of miRNAs and lncRNAs. Based on the integrated matrix combined with similarity
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) ...
...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… ...
Furthermore, the KLSPI method was also evaluated on two nonlinear feedback control problems, including a ship heading control problem and the swing up control of a double-link underactuated pendulum called acrobot. Simulation results illustrate that the proposed method can optimize controller ...
A distributed kernel-based reinforcement learning method is proposed to optimize the multi-robot formation control.Firstly,the basic formation control is r... J Wu,X Xin,C Lian,... - 《Robot》 被引量: 5发表: 2011年 Structured Kernel-Based Reinforcement Learning Kernel-based reinforcement learnin...
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...