[TOMORROW] MaLGa Seminar: Francesco Locatello "Towards Causal Representation Learning", February 2nd 15:00 on Zoom/Youtube
Matteo Santacesaria
Apologies for multiple posting.
We are pleased to announce the next MaLGa Seminar Series -
Statistical Learning and Optimization
Speaker: Francesco Locatello
Affiliation: Amazon
Date: Tuesday, February 2nd, 2021
Time: 15:00 p.m.
Online streaming
Zoom:
https://zoom.us/j/98140186189?pwd=eld3VjR1bkhqK3htTm5aVCtCSFVrQT09
Youtube: https://youtu.be/0Zq1PbPpLug
Title: Towards Causal Representation Learning
Abstract: The two fields of machine learning and graphical
causality arose and developed separately. However, there is now
strong cross-pollination, and increasing interest in both fields
to benefit from the advances of the other. In this talk, I will
discuss my late PhD work, highlighting some points of contact
between causality and machine learning, and proposing key research
questions at the intersection of both. As most work in causality
starts from the premise that the causal variables are observed, a
central problem for AI and causality is causal representation
learning: the discovery of high-level causal variables from
low-level observations.
Bio: The two fields of machine learning and graphical causality
arose and developed separately. However, there is now strong
cross-pollination, and increasing interest in both fields to
benefit from the advances of the other. In this talk, I will
discuss my late PhD work, highlighting some points of contact
between causality and machine learning, and proposing key research
questions at the intersection of both. As most work in causality
starts from the premise that the causal variables are observed, a
central problem for AI and causality is causal representation
learning: the discovery of high-level causal variables from
low-level observations.
Matteo Santacesaria
Assistant Professor
MaLGa - Machine Learning Genoa
Center
Department of Mathematics
University of Genoa
Personal
Homepage
Matteo Santacesaria
Apologies for multiple posting.
We are pleased to announce the next MaLGa Seminar Series -
Statistical Learning and Optimization
Speaker: Francesco Locatello
Affiliation: Amazon
Date: Tuesday, February 2nd, 2021
Time: 15:00 p.m.
Online streaming
Zoom:
https://zoom.us/j/98140186189?pwd=eld3VjR1bkhqK3htTm5aVCtCSFVrQT09
Youtube: https://youtu.be/0Zq1PbPpLug
Title: Towards Causal Representation Learning
Abstract: The two fields of machine learning and graphical
causality arose and developed separately. However, there is now
strong cross-pollination, and increasing interest in both fields
to benefit from the advances of the other. In this talk, I will
discuss my late PhD work, highlighting some points of contact
between causality and machine learning, and proposing key research
questions at the intersection of both. As most work in causality
starts from the premise that the causal variables are observed, a
central problem for AI and causality is causal representation
learning: the discovery of high-level causal variables from
low-level observations.
Bio: Francesco Locatello recently joined Amazon as a Senior
Applied Scientist. He defended his PhD at ETH Zurich, where he was
a Doctoral Fellow at the Max Planck ETH Center for Learning
Systems and ELLIS supervised by Gunnar Rätsch (ETH Zurich) and
Bernhard Schölkopf (Max Planck Institute for Intelligent Systems).
He held a Google PhD Fellowship in Machine Learning and received
the best paper award at the International Conference of Machine
Learning (ICML) 2019.