M.
Postma Bart
(INRIA - team AVIZ)
30/03/2015 14:35
A fundamental way to analyze the brain is by studying brain connectivity, i.e. how brain regions are connected to each other. Two types of brain connectivity exist, anatomical connectivity and functional connectivity, each with their advantages and disadvantages. Being able to study both types of connectivity in concert in real time addresses a need of neuroscientists and neurosurgeons. To...
M.
Bogdan-Ionut Cirstea
(Telecom-ParisTech)
30/03/2015 15:35
Handwriting recognition is a classical AI problem, which has been studied for around 50 years; in its most recent variant, it deals with the recognition of handwritten lines of text. Beyond its inherent importance, handwriting recognition has also served as a testbed for the introduction of some widely used machine learning algorithms, such as the convolutional neural network (CNN) and the...
Dr
Isabelle Guyon
(ChaLearn)
30/03/2015 15:45
We have been organizing in the recent years a number of machine learning challenges with datasets of increasingly large sizes. Particularly demanding are the computer vision and medical imaging tasks. As challenges in machine learning move into the era of big data, it becomes less and less realistic to move data around to let participants enter challenges. Rather, we promote the use of...
Prof.
Michalis Vazirgiannis
(LIX Ecole Polytechnqiue)
30/03/2015 15:55
Understanding and controlling spreading dynamics in networks assumes identification of the most influential nodes that will trigger efficient information diffusion. It has been shown that the best spreaders are the ones located in the k-core of the network rather than those with the highest degree or centrality [Kitsak et al., Nature Physics 6, 888–893 (2010)]. In this paper, we further...
