With the rapid development of multimedia technology, massive unlabelled data with high
dimensionality need to be processed. As a means of dimensionality reduction, unsupervised …

In many fields, such as data mining, machine learning and pattern recognition, datasets
containing large numbers of features are often involved. In such cases, feature selection is …

Due to the rapid development of multimedia technology, a large number of unlabelled data
with high dimensionality need to be processed. The high dimensionality of data not only …

Abstract Online-to-offline/offline-to-online (O2O) business models have attracted lots of
enterprisers to enter this market. In such a fast-growing competition, some studies indicated …

The superimposition of multiple factors has presented a formidable challenge in establishing
the salient features of grain size distribution for the large-scaled complex titanium alloy …

In order to develop an efficient angiosperm-genus classification system, we first collected
petal image of Hibiscus, Orchis, and Prunus, by digital camera, and remove the …

We present a novel regularization method for a multilayer perceptron (MLP) that learns a
regression function in the presence of noise regardless of how smooth the function is. Unlike …

A normative approach called Similarity Matching was recently introduced for deriving and
understanding the algorithmic basis of neural computation focused on unsupervised …

The purpose of this study is to establish rigorous and reliable going concern doubt (GCD)
prediction models. This study first uses the least absolute shrinkage and selection operator …

Background Postoperative pancreatic fistula (POPF) represents the most common
complication following pancreaticoduodenectomy (PD). Predictive models are needed to …