User churn—the sworn enemy of all mobile marketers—refers to those users who abandon an app and never look back. With a sea of apps all competing for attention in an increasingly crowded market, churn ...

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This project aims to predict user churn in the Waze app using machine learning. The focus is on inspecting, organizing, and preparing user activity data to build a churn prediction model.

Due to large number of UEs in a mMTC system, data detection at each access point (AP) becomes a sparse recovery problem. By leveraging the sporadic user activity, we develop a decentralized sparse ...

WTF?! There have been several stories over the years about different governments creating crime-predicting algorithms, leading to comparisons to the 2002 movie Minority Report – even though that ...