In this paper we show that complex (scale-free) network topologies naturally emerge from hyperbolic metric spaces. The hyperbolic geometry can be used to facilitate maximally efï¬...
Fragkiskos Papadopoulos, Dmitri V. Krioukov, Mari&...
We show how features can easily be added to standard generative models for unsupervised learning, without requiring complex new training methods. In particular, each component mul...
Taylor Berg-Kirkpatrick, Alexandre Bouchard-C&ocir...
Abstract. In this work, we are interested in understanding how emotional interactions with a social partner can bootstrap increasingly complex behaviors such as social referencing....
Sofiane Boucenna, Philippe Gaussier, Laurence Hafe...
Abstract. Due to the large size and complex structure of modern networks, firewall policies can contain several thousand rules. The size and complexity of these policies require au...
Abstract-- We present in this paper a way to achieve positioning tasks by visual servoing under complex luminance variations. To do that, we use as visual features the luminance of...