QLS seminar by Alec Boyd via Zoom on 19 October 2021 at 14:00 CET

[Quantitative Life Sciences Section]

Dear All,

On Tuesday, 19 October at 14:00 CET, Dr Alec Boyd (University of 
California, Davis) will give a webinar titled:

"Thermodynamic Machine Learning through Maximum Work Production"

Abstract:
Adaptive systems—such as a biological organism gaining survival 
advantage, an autonomous robot executing a functional task, or a motor 
protein transporting intracellular nutrients—must model the regularities 
and stochasticity in their environments to take full advantage of 
thermodynamic resources. Analogously, but in a purely computational 
realm, machine learning algorithms estimate models to capture 
predictable structure and identify irrelevant noise in training data. 
This happens through optimization of performance metrics, such as model 
likelihood. If physically implemented, is there a sense in which 
computational models estimated through machine learning are physically 
preferred? We introduce the thermodynamic principle that work production 
is the most relevant performance metric for an adaptive physical agent 
and compare the results to the maximum-likelihood principle that guides 
machine learning. Within the class of physical agents that most 
efficiently harvest energy from their environment, we demonstrate that 
an efficient agent’s model explicitly determines its architecture and 
how much useful work it harvests from the environment. We then show that 
selecting the maximum-work agent for given environmental data 
corresponds to finding the maximum-likelihood model. This establishes an 
equivalence between nonequilibrium thermodynamics and dynamic learning. 
In this way, work maximization emerges as an organizing principle that 
underlies learning in adaptive thermodynamic systems.

Indico: http://indico.ictp.it/event/9719/

Zoom Meeting ID to attend the online seminar: 475-819-702

Join Zoom Meeting:https://zoom.us/j/475819702 <https://zoom.us/j/475819702>

If you haven't registered for previous QLS webinars, please contact 
qls at ictp.it to obtain the password for this zoom meeting.

-- 
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