[Forum SIS] Seminario Bayesian Optimization - Università di Bergamo

[Francesco Finazzi]

Per segnalarvi che il giorno *26 ottobre ore 10:30* presso l'Università
degli Studi di Bergamo il dott. Umberto Noè terrà un seminario dal titoto
"On a New Improvement-Based Acquisition Function for Bayesian
Optimization". L'indirizzo di riferimento è:

Aula B04, Edificio B
viale Marconi, 5
Dalmine (BG)

Per maggiori informazioni francesco.finazzi a unibg.it. Seguono abstract e
biografia.


*Abstract*
Bayesian optimization (BO) is a popular algorithm for solving challenging
optimization tasks. It is designed for problems where the objective
function is expensive to evaluate, perhaps not available in exact form,
without gradient information and possibly returning noisy values. Different
versions of the algorithm vary in the choice of the acquisition function,
which recommends the point to query the objective at next. Initially,
researchers focused on improvement-based acquisitions, while recently the
attention has shifted to more computationally
expensive information-theoretical measures. I will present two major
contributions to the literature. First, I propose a new improvement-based
acquisition function that recommends query points where the improvement
is expected to be high with high confidence. The proposed algorithm is
evaluated on a large set of benchmark functions from the global
optimization literature, where it turns out to perform at least as well as
current state-of-the-art acquisition functions, and often better. This
suggests that it is a powerful default choice for BO. The novel policy is
then compared to widely used global optimization solvers in order to
confirm that BO methods reduce the computational costs of the optimization
by keeping the number of function evaluations small. The second
main contribution represents an application to precision medicine, where
the interest lies in the estimation of parameters of a partial differential
equations model of the human pulmonary blood circulation system. Once
inferred, these parameters can help clinicians in diagnosing a patient with
pulmonary hypertension without going through the standard invasive
procedure of right heart catheterization, which can lead to side effects
and complications (e.g. severe pain, internal bleeding, thrombosis).


*Biography*
Umberto Noè is a PhD candidate in Statistics at the University of Glasgow,
and was the first recipient of a scholarship by the prestigious Biometrika
Trust. Currently he is a Scientific Researcher at the German Centre for
Neurodegenerative Diseases in Bonn, Germany. His main research interests
are computational statistics, nonparametric Bayesian inference and causal
inference.

-- 
Francesco Finazzi
Researcher

University of Bergamo
Dept. of Management, Information and Production Engineering
Room 1.09 - Building B
viale Marconi, 5
24044 Dalmine (BG) - Italy

t: 035 205 2363
e: francesco.finazzi a unibg.it
w: www.unibg.it/pers/?francesco.finazzi
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