Consistent Estimation of Multiple Change-Points via Penalized Likelihood

Explore a comprehensive lecture on consistent estimation of multiple change-points via penalized likelihood, presented by Lucas Prates from USP as part of the Extended Program on Randomness and Learning on Networks at IMPA. Delve into advanced topics in discrete Probability and Statistics during this month-long program, featuring talks by participating researchers, minicourses, collaborative work sessions, and open problem discussions. Gain insights into cutting-edge research while networking with international experts and fellow participants. Designed for researchers and PhD students with a strong mathematical background, this program offers a unique opportunity to engage in intensive study and collaboration in a stimulating academic environment.