Android applications are developing rapidly across the mobile ecosystem, but Android
malware is also emerging in an endless stream. Many researchers have studied the …

In recent years, unsupervised feature selection methods have raised considerable interest in
many research areas; this is mainly due to their ability to identify and select relevant features …

本书是清华大学自动化系教材, 主要讨论统计模式识别理论和方法, 第一版包括贝叶斯决策理论,
线性和非线性判别函数, 近邻规则, 经验风险最小化, 特征提取和选择, 以及聚类分析, 等等 …

Atomistic or ab initio molecular dynamics simulations are widely used to predict
thermodynamics and kinetics and relate them to molecular structure. A common approach to …

Recent attempts to achieve fairness in predictive models focus on the balance between
fairness and accuracy. In sensitive applications such as healthcare or criminal justice, this …

We present a machine learning based COVID-19 cough classifier which can discriminate
COVID-19 positive coughs from both COVID-19 negative and healthy coughs recorded on a …

This chapter provides an overview of the support vector regression (SVR), an analytical
technique to investigate the relationship between one or more predictor variables and a real …

This paper demonstrates a new technology that can infer a person's emotions from RF
signals reflected off his body. EQ-Radio transmits an RF signal and analyzes its reflections …

Recently, feature selection and dimensionality reduction have become fundamental tools for
many data mining tasks, especially for processing high-dimensional data such as gene …

Label noise is an important issue in classification, with many potential negative
consequences. For example, the accuracy of predictions may decrease, whereas the …