Geometric Approach to the Lower Estimates of the Supremum of Some Random Processes
INI Seminar Room 2 via YouTube
Lead AI Strategy with UCSB's Agentic AI Program — Microsoft Certified
Google Data Analytics, IBM AI & Meta Marketing — All in One Subscription
Overview
Google, IBM & Meta Certificates — All 10,000+ Courses at 40% Off
One annual plan covers every course and certificate on Coursera. 40% off for a limited time.
Get Full Access
Explore a mathematical seminar lecture where Professor Boris Kashin from the Steklov Mathematical Institute of the Russian Academy of Sciences presents geometric approaches for determining lower estimates of supremum in random processes. Delivered as part of the Discretization and Recovery in High-Dimensional Spaces (DRE) programme at the Isaac Newton Institute, delve into advanced mathematical concepts through this 53-minute presentation. Learn from one of the leading mathematical scientists as he shares insights at this prestigious research institute, known for fostering international collaboration and advancing mathematical sciences with applications across science and technology fields.
Syllabus
Prof. Boris Kashin | Geometric approach to the lower estimates of the supremum of some random...
Taught by
INI Seminar Room 2