Stochastic relational models (SRMs) [15] provide a rich family of choices for learning and predicting dyadic data between two sets of entities. The models generalize matrix factor...
This paper proposes a new approach to describe the salient contours in cluttered scenes. No need to do the preprocessing, such as edge detection, we directly use a set of random s...
The application of Reinforcement Learning (RL) algorithms to learn tasks for robots is often limited by the large dimension of the state space, which may make prohibitive its appli...
Andrea Bonarini, Alessandro Lazaric, Marcello Rest...
There are very few instances in which positive Darwinian selection has been convincingly demonstrated at the molecular level. In this study, we present a novel test for detecting p...
Tal Pupko, Roded Sharan, Masami Hasegawa, Ron Sham...
We investigate a recently proposed method for the analysis of oscillatory patterns in EEG data, with respect to its capacity of further quantifying processes on slower (< 1 Hz)...