Recommender systems have been widely used in different application domains including
energy-preservation, e-commerce, healthcare, social media, etc. Such applications require …

The emerging Federated Learning (FL) permits all workers (eg, mobile devices) to
cooperatively train a model using their local data at the network edge. In order to avoid the …

Federated learning (FL) enables multiple devices to collaboratively train a shared machine
learning (ML) model while keeping all the local data private, which is a crucial enabler to …

Tensor factorization has been proved as an efficient unsupervised learning approach for
health data analysis, especially for computational phenotyping, where the high-dimensional …

FL is a futuristic research topic that enables cross-sectoral training in ML systems in various
organizations with some privacy restrictions. This review article establishes the extensive …

Machine learning (ML) and artificial intelligence (AI) technologies are becoming intrinsic in
our every-day life. These technologies are present in our vehicles, our customer service …

Modern healthcare systems are collecting a huge volume of healthcare data from a large
number of individuals with various medical procedures, medications, diagnosis, lab tests …