Monthly Archives: January 2017

Talk by Max Welling

You are all cordially invited to the AMLab seminar on Tuesday January 31 at 16:00 in C3.163, where Max Welling will give a talk titled “AMLAB/QUVA’s progress in Deep Learning”. Afterwards there are the usual drinks and snacks!

Abstract: I will briefly describe the progress that has been made in the past year in AMLAB and QUVA in terms of deep learning. I will try to convey a coherent story of how some of these projects tie together into a bigger vision for the field. I will end with research questions that seem interesting for future projects.

Talk by Marco Loog (TUD)

You are all cordially invited to the AMLab seminar on Tuesday January 24 at 16:00 in C3.163, where Marco Loog will give a talk titled “Semi-Supervision, Surrogate Losses, and Safety Guarantees”. Afterwards there are the usual drinks and snacks!

Abstract: Users of classification tools tend to forget [or worse, might not even realize] that classifiers typically do not minimize the 0-1 loss, but a surrogate that upperbounds the classification error on the training set.  Here we argue that we should also study these losses as such and we consider the problem of semi-supervised learning from this angle.  In particular, we look at the basic setting of linear classifiers and convex margin-based losses, e.g. hinge, logistic, squared, etc.  We investigate to what extent semi-supervision can be safe at least on the training set, i.e., we want to construct semi-supervised classifiers for which the empirical risk is never larger than the risk achieved by their supervised counterparts.  [Based on work carried out together with Jesse Krijthe; see https://arxiv.org/abs/1612.08875 and https://arxiv.org/abs/1503.00269].