This paper proposes an efficient algorithm to perform privacy-preserving (PP) facial
expression classification (FEC) in the client-server model. The server holds a database and …

Individuals and companies, taking advantage of cloud computing which affords both
resource and compute scalability, are willing to outsource their exploding data to save the …

Facial phenotyping for medical prediagnosis has recently been successfully exploited as a
novel way for the preclinical assessment of a range of rare genetic diseases, where facial …

Advancements in deep learning enable neural network (NN) inference to be a service, but
service providers and clients want to keep their inputs secret for privacy protection. Private …

Privacy-preserving data mining (PPDM) is an emergent research area that addresses the
incorporation of privacy preserving concerns to data mining techniques. In this paper we …

Abstract Machine learning (ML) classification has been one of the most important techniques
of popular Internet services that aim to provide accurate predictions of data by means of a …

As a classifier, support vector machine (SVM) explains a core problem of machine learning,
namely sample classification in statistical terms. It has been widely used in machine …

Clustering is a common task for organizing data into clusters. The kernel k-means identifies
clusters of nonlinearly separable data by applying the kernel trick to the commonly used k …

Data classification is a widely used data mining technique for big data analysis. By training
massive data collected from the real world, data classification helps learners discover …

A k-means clustering with a new privacy-preserving concept, user-centric privacy
preservation, is presented. In this framework, users can conduct data mining using their …