2 QLS Seminars - Wed. 28 February at 10:00am and 2:30pm

[Quantitative Life Sciences]

On Wednesday, 28 February  at 10:00 CET, Yizhou Xu (Tsinghua University, 
China.) will give a seminar titled:

_Fast renormalizing the structures and dynamics of ultra-large systems 
via random renormalization group_*_
_ *

_Abstract:
_Criticality and symmetry, studied by the renormalization groups, lie at 
the heart of modern physics theories of matters and complex systems. 
However, surveying these properties with massive experimental data is 
bottlenecked by the intolerable costs of computing renormalization 
groups on real systems. Here, we develop a time- and memory-efficient 
framework, termed as the random renormalization group, for renormalizing 
ultra-large systems (e.g., with millions of units) within minutes. This 
framework is based on random projections, hashing techniques, and kernel 
representations, which support the renormalization governed by linear 
and non-linear correlations. For system structures, it exploits the 
correlations among local topology in kernel spaces to unfold the 
connectivity of units, identify intrinsic system scales, and verify the 
existences of symmetries under scale transformation. For system 
dynamics, it renormalizes units into correlated clusters to analyze 
scaling behaviours, validate scaling relations, and investigate 
potential criticality. Benefiting from hashing-function-based designs, 
our framework significantly reduces computational complexity compared 
with classic renormalization groups, realizing a single-step 
acceleration of two orders of magnitude. Meanwhile, the efficient 
representation of different kinds of correlations in kernel spaces 
realized by random projections ensures the capacity of our framework to 
capture diverse unit relations. As shown by our experiments, the random 
renormalization group helps identify non-equilibrium phase transitions, 
criticality, and symmetry in diverse large-scale genetic, neural, 
material, social, and cosmological systems.

_
_
_The seminar will take place in the *Common area*, Ex SISSA building, 
Second floor, via Beirut 2
_ _
_Indico webpage: https://indico.ictp.it/event/10661/
__
You are all most welcome to attend!
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At 14:30  Lorenzo ROSASCO (University of Genoa, Italy) will give a 
seminar titled

_Learning functions, operators and dynamical systems with kernels_

_Abstract_:
Supervised machine learning is concerned with the problem of estimating 
a function of interest from a random set of input/output pairs. While 
classically real-valued functions are considered, there is a growing 
interest in estimating more complex maps such as linear and nonlinear 
operators.

In this talk, I will describe how some of these questions can be tackled 
using kernel methods.
I will show how classical results for scalar-valued functions seamlessly 
extend to operators. Then, I will describe how this approach can be used 
to learn dynamical systems by estimating the corresponding Koopman operator.


_Venue: Kastler Lecture Hall, Adriatico Guest House, Riva Massimiliano e 
Carlotta, Grignano I - 34151 Trieste _




You are all most welcome to attend!

Best regards,
Erica

-- 
Erica Sarnataro
Group Secretary
Quantitative Life Sciences
The Abdus Salam International Centre for Theoretical Physics (ICTP)
Trieste,  Italy
Tel. +39-040-2240623
www.ictp.it/research/qls.aspx
e-mail:qls at ictp.it