The prosperity of machine learning has been accompanied by increasing attacks on the
training process. Among them, poisoning attacks have become an emerging threat during …

Latent-factor models (LFM) based on collaborative filtering (CF), such as matrix factorization
(MF) and deep CF methods, are widely used in modern recommender systems (RS) due to …

The flipped classroom approach is aimed at improving learning outcomes by promoting
learning motivation and engagement. Recommendation systems can also be used to …

A book at the intersection of data science and media studies, presenting concepts and
methods for computational analysis of cultural data. How can we see a billion images? What …

On many online platforms, users can engage with millions of pieces of content, which they
discover either organically or through algorithmically-generated recommendations. While …

Predicting Click-Through Rate (CTR) in billion-scale recommender systems poses a long-
standing challenge for Graph Neural Networks (GNNs) due to the overwhelming …

Recommendation systems for Web content distribution intricately connect to the information
access and exposure opportunities for vulnerable populations. The emergence of Large …

As the reach of science content in traditional media declines, many institutions and scientists
are turning to YouTube as a powerful tool for communicating directly with non-expert …

YouTube has become one of the largest websites on the Internet. Among its many genres,
both professional and amateur science communicators compete for audience attention. This …

To support rapidly increasing services and applications from users, multi-tier computing is
emerged as a promising system-level computing architecture by distributing …