With the increasing role of ICT in enabling and supporting smart cities, the demand for big
data analytics solutions is increasing. Various artificial intelligence, data mining, machine …

In recent years, there has been remarkable growth in Federated Learning (FL) approaches
because they have proven to be very effective in training large Machine Learning (ML) …

A federated learning (FL) scheme (denoted as Fed-KSVM) is designed to train kernel
support vector machines (SVMs) over multiple edge devices with low memory consumption …

Big Data Systems (Hadoop, DBMSs) require a complicated setup and tuning to store and
process big data on a parallel cluster. This is mainly due to static partitioning when data sets …

Abstract Machine learning (ML) on Big Data has gone beyond the capacity of traditional
machines and technologies. ML for large scale datasets is the current focus of researchers …

With todays' modern technology and lifestyle, vast amounts of data are generated
exponentially day by day. Storing, processing, and analyzing such huge data is a complex …

The advancement in technology has resulted in large size of data, which then introduce
challenges to labelling or classification tasks with high dimensional features. Specifically, in …

In general, it is no secret that each apartment has a special microclimate. This concept
includes temperature conditions, light, humidity and many other parameters. All of them …

In big data environments, utilizing a parallel Support Vector Machine (SVM) can significantly
expedite the training process. However, prior efforts have faced challenges due to the …

In recent years, sleep apnea has emerged as a major contributor to the epidemic of sleep
disturbances that has emerged in modern society. Due to the high price, unpleasant …