May 15 – May 28, 2022
8:30 a.m. – 18:00 p.m.
Location: See agenda for details of location each day
This scientific meeting will concentrate on stochastic algorithms and their rigorous numerical analysis for various problems, including statistical learning, optimization and approximation. Stochastic algorithms are valuable tools when addressing challenging computational problems. For instance, machine learning, stochastic optimal control, data assimilation, and bayesian statistics are hot research areas where these algorithms exhibit their strength. The realm of applications is immense and of great interest to KAUST and the Kingdom. CEMSE is flexible in having contributions that either offer mathematical foundations to algorithmic analysis or showcase relevant applications.
As a part of this workshop, CEMSE will offer two mini-courses:
– Deep neural network robustness, by Prof. Bernard Ghanem (KAUST); May 19.
– Machine learning methods in computational finance: from signatures to reinforcement learning, by Christian Bayer (WIAS Berlin), Christoph Belak (TU-Berlin), Blanka Horvath (TU-Munich) and Paul Hager (Humboldt University); May 22, 23 and 24.
Call for posters
The conference program will present an opportunity for Ph.D. students and postdocs to present their research work in a poster session taking place on Monday, May 23, 2022, from 5:00 to 6:00 p.m. at the KAUST Library. The deadline for submissions is Wednesday, May 16, 2022.
Registration
Registration for the event and the poster session is open through the link below.
To find out more about the conference and complete event details, please visit our website.
This event is organized by Stochastic Numerics PI Professor Raul Tempone (Chair) and Computational Probability PI Professor Ajay Jasra (Co-Chair) with financial support from KAUST.
