Invitation to the Joint ICTP-SISSA Webinar Colloquium by Prof. Andrea Montanari, Stanford University, on "What is Machine Learning and What We Don't Understand About It", on Wednesday 22 July at 16:00 hrs
director at ictp.it
Fri Jul 17 14:27:24 CEST 2020
You are most cordially invited to the Joint ICTP-SISSA Webinar
Colloquium byProf. Andrea Montanari, Stanford University, USA on "What
is Machine Learning and What We Don't Understand About It", on Wednesday
22 July at 16:00 hrs.
Pre-registration is required at the following url:
After registering, you will receive a confirmation email containing
information about joining the webinar.
The talk will be available on livestream via the ICTP website, and also
on ICTP's YouTube channel.
Live screening in the Budinich Lecture Hall will be set up as well. Due
to the safety measures that are in place, a maximum of 10 can attend by
keeping distances and wearing a mask).
*Biosketch: *Andrea Montanari received a Laurea degree in Physics in
1997, and a Ph. D. in Theoretical Physics in 2001 (both from Scuola
Normale Superiore in Pisa, Italy). He has been post-doctoral fellow at
Laboratoire de Physique Théorique de l'Ecole Normale Supérieure
(LPTENS), Paris, France, and the Mathematical Sciences Research
Institute, Berkeley, USA. Since 2002 he is Chargé de Recherche (with
Centre National de la Recherche Scientifique, CNRS) at LPTENS. In
September 2006 he joined Stanford University as a faculty, and since
2015 he is Full Professor in the Departments of Electrical Engineering
and Statistics. He was co-awarded the ACM SIGMETRICS best paper award in
He received the CNRS bronze medal for theoretical physics in 2006, the
National Science Foundation CAREER award in 2008, the Okawa Foundation
Research Grant in 2013, and the Applied Probability Society Best
Publication Award in 2015. He is an Information Theory Society
distinguished lecturer for 2015-2016. In 2016 he received the James L.
Massey Research & Teaching Award of the Information Theory Society for
young scholars, and in 2017 was elevated to IEEE Fellow. In 2018 he was
an invited sectional speaker at the International Congress of
Mathematicians. He is an invited IMS Medallion lecturer for the 2020
Bernoulli-IMS World Congress.
*Abstract: *The last fifteen years have witnessed dramatic breakthroughs
in machine learning. This progress was crucially driven by engineering
advances: greater computing power and larger availability of training
data. Not only the collection of methods that emerged from this
revolution are not well understood mathematically, but they actually
appear to defy traditional mathematical theories of machine learning.
Future developments and applications, especially within the sciences,
will require to understand better the underlying mathematical
principles. I will try to provide a gentle introduction to the subject,
and a peek into some recent advances towards addressing these challenges.
The talk will be followed by a question/answer session.
For info, please check the following link: http://indico.ictp.it/event/9419/
We look forward to seeing you online!
With best regards,
Office of the Director, ICTP
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