Social interactions unfold over time, at multiple time scales, and can be observed through multiple sensory modalities. In this paper, we propose a machine learning framework for ...
Ian R. Fasel, Masahiro Shiomi, Pilippe-Emmanuel Ch...
Privacy is an enormous problem in online social networking sites. While sites such as Facebook allow users fine-grained control over who can see their profiles, it is difficult ...
This paper presents a new architecture of neural networks designed for pattern recognition. The concept of induction graphs coupled with a divide-and-conquer strategy defines a Gr...
We present a novel phoneme-based student model for spelling training. Our model is data driven, adapts to the user and provides information for, e.g., optimal word selection. We de...
Recommender systems are important to help users select relevant and personalised information over massive amounts of data available. We propose an unified framework called Prefer...