Stochastic Numerics and Statistical Learning: Theory and Applications Workshop 2024
The Stochastic Numerics and Statistical Learning: Theory and Applications Workshop 2024 is an engaging and insightful event for researchers, faculty members and students interested in stochastic algorithms, statistical learning, optimization and approximation. This year, the workshop focuses on contributions that offer mathematical foundations for algorithmic analysis or highlight relevant applications.
About
We are excited to announce the upcoming Stochastic Numerics and Statistical Learning: Theory and Applications Workshop 2024, taking place from May 19-30, 2024. Following the highly successful previous two years' editions, this year's workshop promises to be another engaging and insightful event for researchers, faculty members and students interested in stochastic algorithms, statistical learning, optimization and approximation.
The 2024 workshop aims to build on the achievements of last year's event, which featured 30 talks, two mini-courses and two poster sessions, attracting over 150 participants from various universities and research institutes. In 2022 and 2023, attendees had the opportunity to learn from insightful talks, interactive mini-courses and vibrant poster sessions.
This year, the workshop will once again showcase contributions that offer mathematical foundations for algorithmic analysis or highlight relevant applications. Confirmed speakers include renowned experts from institutions such as Ecole Polytechnique, EPFL, Université Pierre et Marie Curie - Paris VI, CUHK Shenzhen and Imperial College London, among others.
The 2024 workshop will feature:
- Engaging talks and presentations by leading experts in the field.
- Two poster sessions on May 20 (Building 20 session) and May 27 (Building 9 session), providing an opportunity for participants to present their research.
- Two minicourses on "Quantum Computing for Finance” by Prof. Antoine Jacquier and “Scaling limits of random neural networks” by Prof. Cristopher Salvi.
We encourage researchers, faculty members and students from all disciplines to attend this workshop to broaden their understanding of stochastic numerics and statistical learning. Participants will have the opportunity to network with experts, explore potential applications and foster collaborations across various research areas.
For more information about the event, including confirmed speakers, schedules and minicourse details, please visit the link.