State-of-the-art Deep Neural Networks (DNNs) are typically too cumbersome to be
practically useful in portable electronic devices. As such, several works pursue model …

In this work, we present a novel embedded feature selection method based on a Multi-layer
Perceptron (MLP) network and generalize it for group-feature or sensor selection problems …

Abstract Sustainable Development Goals (SDGs) are developments that maintain
sustainable improvement in society's economic, social, and environmental welfare …

Estimation of regression parameters using the Least Squares (LS) method could not be
performed when the number of explanatory variables exceeds the number of observations …

High-dimensional data has more variables than observations (p>> n). In this case, modeling
with regression analysis becomes ineffective because it will violate the multicollinearity …

Analytical chemistry plays a crucial role in various fields as it it covers identification, quan-
tification, and characterization of chemical substances. It is essential for understanding the …

Learning-based approaches have recently become popular for various computer vision
tasks such as facial expression recognition, action recognition, banknote identification …

Data berdimensi tinggi merupakan data dengan karakteristik jumlah variabel bebas yang
lebih banyak daripada amatan. Data seperti ini seringkali memunculkan masalah, seperti …

One of the rainfall prediction techniques is the Statistical Downscaling Modeling (SDS). SDS
modeling is one of the applications of modeling with covariates conditions that are generally …

This thesis will pursue statistical learning methods and missing data imputation techniques
in order to develop a precision medicine model, predicting treatment outcome heterogeneity …