Dear all,
In November we will have two in person talks in the thematic seminar
in rapid succession at the UvA.
- On Thursday November 10 Damien Garreau from the Université Côte
d'Azur will speak about his analysis of the popular LIME method for
explainable machine learning.
- And on November 14 or 15, Umut Şimşekli from INRIA/École Normale
Supérieure will speak about his new generalization bounds for deep
neural networks.
Damien Garreau (Université Côte d'Azur, https://sites.google.com/view/damien-garreau/home)
Thursday November 10, 16h00-17h00
In person, at the University of Amsterdam
Room: TBA
What does LIME really see in images?
The performance of modern algorithms on certain computer vision
tasks such as object recognition is now close to that of humans.
This success was achieved at the price of complicated architectures
depending on millions of parameters and it has become quite
challenging to understand how particular predictions are made.
Interpretability methods propose to give us this understanding. In
this talk, I will present a recent result about LIME, perhaps one of
the most popular methods.
Upcoming talks:
- Nov. 14 or 15, Umut Şimşekli from
INRIA/École Normale Supérieure will speak about new generalization
bounds for deep neural networks.
Seminar organizers:
Tim van Erven
Botond Szabo
https://mschauer.github.io/StructuresSeminar/
--
Tim van Erven <tim@timvanerven.nl>
www.timvanerven.nl