[Colloquium] TODAY, 4:30: Data Science/Stats Candidate Talk - Krikamol Muandet (Max Planck Institute)

[Rob Mitchum]

*Data Science Institute/Statistics Candidate Seminar*


*Krikamol Muandet*
*Research Group Leader*

*Max Planck Institute for Intelligent Systems (MPI-IS), Tübingen, Germany*

*Monday, February 7th*
*4:30 p.m. - 5:30 p.m.*
*In-Person: John Crerar Library, Room 390*
*Remote: Live Stream <http://live.cs.uchicago.edu/krikamolmuandet/> or Zoom
<https://uchicago.zoom.us/j/99702907589?pwd=SE1GSkNwR1N1WHpoMzcwbWhvUWY3dz09>
(details
below)*

*Abstract*: Society is made up of a set of diverse individuals, demographic
groups, and institutions. Therefore, learning and deploying algorithmic
models across heterogeneous environments face a set of various trade-offs.
In order to develop reliable machine learning algorithms that can interact
successfully with the real world, it is necessary to deal with changes in
underlying data-generating distributions. This talk will be about the
kernel mean embedding (KME), a nonparametric kernel-based framework to
represent probability distributions and model changes thereof. In
particular, I will focus on how this framework can help improve the
credibility of algorithmic decision-making by enabling us to reason about
higher-order causal effects of policy interventions as well as by removing
the effect of unobserved confounders through the use of an instrumental
variable (IV). Lastly, I will argue that a better understanding of the ways
in which our data are generated and how our models can influence them will
be crucial for reliable machine learning systems, especially when gaining
full information about data may not be possible.

*Bio*: Krikamol Muandet <http://www.krikamol.org/> is currently a research
group leader in the Empirical Inference Department at the Max Planck
Institute for Intelligent Systems (MPI-IS), Tübingen, Germany. Previously,
he was a lecturer in the Department of Mathematics at Mahidol University,
Bangkok, Thailand. He received his Ph.D. in computer science from the
University of Tübingen in 2015 working mainly with Prof. Bernhard
Schölkopf. He received his master’s degree in machine learning from
University College London (UCL), the United Kingdom where he worked mostly
with Prof. Yee Whye Teh at Gatsby Computational Neuroscience Unit. He
served as a publication chair of AISTATS 2021 and as an area chair for
AISTATS 2022, NeurIPS 2021, NeurIPS 2020, NeurIPS 2019, and ICML 2019,
among others.

*Host*: Victor Veitch

*Zoom Info:*
https://uchicago.zoom.us/j/99702907589?pwd=SE1GSkNwR1N1WHpoMzcwbWhvUWY3dz09
Meeting ID: 997 0290 7589
Passcode: ds2022


-- 
*Rob Mitchum*

*Associate Director of Communications for Data Science and Computing*
*University of Chicago*
*rmitchum at uchicago.edu <rmitchum at ci.uchicago.edu>*
*773-484-9890*
-------------- next part --------------
An HTML attachment was scrubbed...
URL: <http://mailman.cs.uchicago.edu/pipermail/colloquium/attachments/20220207/8650529c/attachment.html>