arXiv ·
Researchers studied user lifetime prediction in the location-based social network Jodel within Saudi Arabia, leveraging its disjoint communities. Machine learning models, particularly Random Forest, were trained to predict user lifetime as a regression and classification problem. A single countrywide model generalizes well and performs similarly to community-specific models.
KAUST ·
KAUST is increasing campus population due to repatriation flights and additional students coming to campus. There has been a noticeable uptick in new cases of COVID-19, with some presenting with symptoms. KAUST emphasizes the importance of wearing face coverings, observing physical distance, washing hands, avoiding groups of more than 10 people and restricting social networks. Why it matters: This update provides insight into the university's health and safety protocols, reflecting broader trends in managing public health within research institutions in the GCC.
MBZUAI ·
This article discusses a talk by Gábor Lugosi on "network archaeology," specifically the problems of root finding and broadcasting in large networks. The talk addresses discovering the past of dynamically growing networks when only a present-day snapshot is observed. Lugosi's research interests include machine learning theory, nonparametric statistics, and random structures. Why it matters: Understanding the evolution and origins of networks is crucial for various applications, including analyzing social networks, biological systems, and the spread of information.