AIMC Topic: Normal Distribution

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A causal discovery algorithm based on the prior selection of leaf nodes.

Neural networks : the official journal of the International Neural Network Society
In recent years, Linear Non-Gaussian Acyclic Model (LiNGAM) has been widely used for the discovery of causal network. However, solutions based on LiNGAM usually yield high computational complexity as well as unsatisfied accuracy when the data is high...

On the minimax optimality and superiority of deep neural network learning over sparse parameter spaces.

Neural networks : the official journal of the International Neural Network Society
Deep learning has been applied to various tasks in the field of machine learning and has shown superiority to other common procedures such as kernel methods. To provide a better theoretical understanding of the reasons for its success, we discuss the...

SVR-EEMD: An Improved EEMD Method Based on Support Vector Regression Extension in PPG Signal Denoising.

Computational and mathematical methods in medicine
Photoplethysmography (PPG) has been widely used in noninvasive blood volume and blood flow detection since its first appearance. However, its noninvasiveness also makes the PPG signals vulnerable to noise interference and thus exhibits nonlinear and ...

Exploiting the stimuli encoding scheme of evolving Spiking Neural Networks for stream learning.

Neural networks : the official journal of the International Neural Network Society
Stream data processing has lately gained momentum with the arrival of new Big Data scenarios and applications dealing with continuously produced information flows. Unfortunately, traditional machine learning algorithms are not prepared to tackle the ...

Computer-Aided Diagnosis of Multiple Sclerosis Using a Support Vector Machine and Optical Coherence Tomography Features.

Sensors (Basel, Switzerland)
The purpose of this paper is to evaluate the feasibility of diagnosing multiple sclerosis (MS) using optical coherence tomography (OCT) data and a support vector machine (SVM) as an automatic classifier. Forty-eight MS patients without symptoms of op...

Super-Resolution for Improving EEG Spatial Resolution using Deep Convolutional Neural Network-Feasibility Study.

Sensors (Basel, Switzerland)
Electroencephalography (EEG) has relatively poor spatial resolution and may yield incorrect brain dynamics and distort topography; thus, high-density EEG systems are necessary for better analysis. Conventional methods have been proposed to solve thes...

The influence of diffusion cell type and experimental temperature on machine learning models of skin permeability.

The Journal of pharmacy and pharmacology
OBJECTIVES: The aim of this study was to use Gaussian process regression (GPR) methods to quantify the effect of experimental temperature (T ) and choice of diffusion cell on model quality and performance.

Dual Model Medical Invoices Recognition.

Sensors (Basel, Switzerland)
Hospitals need to invest a lot of manpower to manually input the contents of medical invoices (nearly 300,000,000 medical invoices a year) into the medical system. In order to help the hospital save money and stabilize work efficiency, this paper des...

Machine learning discovery of longitudinal patterns of depression and suicidal ideation.

PloS one
BACKGROUND AND AIM: Depression is often accompanied by thoughts of self-harm, which are a strong predictor of subsequent suicide attempt and suicide death. Few empirical data are available regarding the temporal correlation between depression symptom...