Deep Learning

Sequential Variational Autoencoders for Collaborative Filtering

Variational autoencoders were proven successful in domains such as computer vision and speech processing. Their adoption for modeling user preferences is still unexplored, although recently it is starting to gain attention in the current literature. …

Predicting Temporal Activation Patterns via Recurrent Neural Networks

We tackle the problem of predict whether a target user (or group of users) will be active within an event stream before a time horizon. Our solution, called PATH, leverages recurrent neural networks to learn an embedding of the past events. The …

Differential Privacy and Neural Networks: A Preliminary Analysis

The soaring amount of data coming from a variety of sources including social networks and mobile devices opens up new perspectives while at the same time posing new challenges. On one hand, AI-systems like Neural Networks paved the way toward new …