Partnership Program LMU - Tel Aviv University
Data Science – Combining Statistics and Computer Science
Workshop
Munich, 8. November 2018
This workshop intends to promote Data Science building on the essential contributions of both, Statistics and Computer Science. Both universities, LMU and Tel Aviv University (TAU) have recently established a track record in the field of Data Science.
The LMU hosts the Elite Master program Data Science (www.datascience-munich.de) which is run jointly by the departments of statistics and computer science and is funded by the Bavarian state within the Elitenetzwerk Bayern.
At TAU, recently a Data Science Center has been established which aims to bundle the activities in this direction (https://datascience.tau.ac.il/).
Both groups emphasize the definition of Data Science as the intersection of statistics and computer science, which holds in research as well as in education.
The goal of the workshop is to explore the potential of collaboration between data scientists from TAU and LMU.
We envisage not only joint research activities but also a mutual exchange of students in the corresponding master programs. Potentially interdisciplinary collaborations between data scientists and researchers in the application field is a further goal of the workshop.
Conference Venue
The workshop takes place at Ludwig-Maximilians-Universität, Bibliothek der Wirtschaftswissenschaften und Statistik,
Freskensaal - R115 (1st floor), Ludwigstrasse 28. (google maps)
Registration
for this workshop ends on Friday, November 2, 2018. Please register with iris.burger@stat.uni-muenchen.de
Workshop Program
09:00 – 09:10 OPENING
09:10 - 09:20
TBA
LMU-TAU Research Cooperation Program
09:20 - 09:35
Goeran Kauermann, Munich
Data Science @ LMU/Germany
09:35 - 09:50
David M. Steinberg, Tel Aviv
Data Science @ TAU/Israel
09:50 - 10:00
All Participants
Discussion and First Thoughts
10:00 - 10:20 COFFEE BREAK
10:20 - 11:00
Amir Globerson, Tel Aviv
Deep Learning: Optimization, Generalization and Architectures
11:00 - 11:40
Moritz Grosse-Wentrup, Munich
Causal Representation Learning
11:40 - 12:30
Saharon Rosset, Tel Aviv
Quality Preserving Databases: Statistically Sound and Efficient Use of Public Databases for an Infinite Sequence of Tests
12:30 - 14:00 LUNCH BREAK
14:00 - 14:40
Volker Schmid, Munich
Efficient Bayesian approaches in Data Science
14:40 - 15:20
Daniel Nevo, Tel Aviv
On classical and modern variable selection in regression
15:20 - 15:40 COFFEE BREAK
15:40 - 16:20
David M. Steinberg, Tel Aviv
Experimental Design in the Online Economy
16:20 - 17:00
Goeran Kauermann, Munich
The Pipeline Revisited - Combining Machine Learning and Statistics
17:00 - 17:30
All Participants
Open Discussion
19:30 DINNER