Nowadays, as the number of items is increasing and the number of items that users have
access to is limited, user-item preference matrices in recommendation systems are always …

The widespread use of E-commerce websites has drastically increased the need for
automatic recommendation systems with machine learning. In recent years, many ML-based …

Along with the information increase on the Internet, there is a pressing need for online and
real-time recommendation in commercial applications. This kind of recommendation attains …

Many modern commercial sites employ recommender systems to propose relevant content
to users. While most systems are focused on maximizing the immediate gain (clicks …

Algorithms for sparse recovery problems from non-linear measurements have attracted
some attention lately. Closely related to the problem of sparse is recovery is the problem of …