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”The physics of
inference, phase transitions, and
the detection of
communities in networks”
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Date: |
Download-files: |
Time: |
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Thursday, 24 March 2022 |
Video-Recording for any system with MP4-support - Video.mp4 (ca. 412 Mb) |
15:15 – 16:30
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Speaker today: Cristopher
Moore (Santa Fe Institute)
Abstract:
There is a deep analogy between Bayesian
inference and statistical physics.
When we fit a model to noisy data, we can
think about the “energy landscape"
of possible models, and look
for phase transitions where the ground truth
suddenly
gets lost in this landscape — either because of thermal equilibrium
(where “heat” is
noise) or because of dynamics (e.g. a metastable state
trapped
behind
a free energy barrier). I’ll use this framework to describe phase transitions
in community detection in
networks, where communities suddenly become hard
or impossible to find. If time
permits, I’ll discuss related spectral algorithms,
and give a hint of similar
phase transitions in other inference problems.
Biography:
Cristopher
Moore received his B.A. in Physics, Mathematics, and Integrated Science
from Northwestern University,
and his Ph.D. in Physics from Cornell.
From 2000 to 2012 he was a professor at
the University of New Mexico,
with joint appointments in
Computer Science and Physics. Since 2012,
Moore has been a resident professor at the
Santa Fe Institute.
He has also held visiting positions at the
Niels Bohr Institute,
École
Normale Superieure, École Polytechnique, Université Paris 7,
Northeastern University, the University of
Michigan, and Microsoft Research.
Moore has written over 160 papers at the
boundary between mathematics, physics,
and computer science, ranging
from quantum computing, to phase transitions
in Bayesian inference and
NP-complete problems, to the theory of
social networks.
He is an elected Fellow of the American
Physical Society, the American
Mathematical Society,
and the American Association for the Advancement of Science.
With Stephan Mertens,
he is the author of The Nature of Computation from
Oxford
University Press.