Since its inception in the 19th century through the efforts of Poincaré
and Lyapunov, the theory of dynamical systems addresses the qualitative
behaviour of dynamical systems as understood from models. From this
perspective, the modeling of dynamical processes in applications
requires a detailed understanding of the processes to be analyzed. This
deep understanding leads to a model, which is an approximation of the
observed reality and is often expressed by a system of Ordinary/Partial,
Underdetermined (Control), Deterministic/Stochastic differential or
difference equations. While models are very precise for many processes,
for some of the most challenging applications of dynamical systems (such
as climate dynamics, biological systems or the financial markets), the
development of such models is notably difficult.
On the other
hand, the field of machine learning is concerned with algorithms
designed to accomplish a certain task, whose performance improves with
the input of more data. Applications for machine learning methods
include computer vision, stock market analysis, speech recognition,
recommender systems and sentiment analysis in social media. The machine
learning approach is invaluable in settings where no explicit model is
formulated, but measurement data is available. This is frequently the
case in many systems of interest, and the development of data-driven
technologies is becoming increasingly important in many applications.
The intersection of the fields of dynamical systems and machine
learning is largely unexplored, and the goal of this symposium is to
bring together researchers from these fields to fill the gap between the
theories of dynamical systems and machine learning in the following directions:
- Machine Learning for Dynamical Systems: how to analyze
dynamical systems on the basis of observed data rather than attempt to
study them analytically.
- Dynamical Systems for Machine Learning: how to analyze algorithms of Machine Learning using tools from the theory of dynamical systems.
Organizers: Boumediene Hamzi, Yi-Ke Guo, Jeroen Lamb, Diana O'Malley (Imperial College London) and Robert MacKay (University of Warwick and The Alan Turing Institute)
NB: Please send an email to email@example.com if you are interested in giving a talk.
|Location||Imperial College London, UK|
|ConferenceDates||February 11–13, 2019|