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5 hours ago · The statistical representation of the Gaussian process method used in the study is as follows: ... Rasmussen, C.E. Gaussian processes in machine learning. In ...
9 hours ago · This paper proposes a machine learning approach, leveraging Gaussian Process (GP) and Krill Herd Algorithm (KHA), for energy management in renewable ...
15 hours ago · (11) presents a “curvilinear distance metric learning (CDML)” technique that dynamically learns the nonlinear geometries of the training data. The CDML is ...
18 hours ago · This chapter delves into the machine learning (ML) techniques that surround and enable network traffic monitoring and analysis (NTMA) and video quality ...
9 hours ago · With tdescore, we aim to develop an alternative to this resource- intensive process using a machine-learning approach. ... univariate Gaussian process model ...
11 hours ago · In contrast to ANNs, Gaussian process regression (GPR) is based on nonparametric modeling principles as well as on fundamental statistical knowledge and hence ...
8 hours ago · Named Entity Recognition Under Domain Shift via Metric Learning for Life Sciences · Hongyi Liu | Qingyun Wang | Payam Karisani | Heng Ji. Named entity ...
7 hours ago · ... Gaussian process regression-based method. SPARK identifies SVGs based on a spatial generalized linear mixed model with multiple spatial kernels, directly ...
11 hours ago · Considering the commonly used Gaussian noise model as an example, the ... The ERDB metric can measure the fluctuation of image total energy during the iteration.
22 hours ago · We present open-source tools for three-dimensional (3D) analysis of photographs of dissected slices of human brains, which are routinely acquired in brain ...