Fitting Manifolds to Data with Large Noise by Hari Narayanan

Explore the challenges and techniques of fitting manifolds to data with significant noise in this lecture by Hari Narayanan. Delve into advanced data science concepts as part of the "Data Science: Probabilistic and Optimization Methods" discussion meeting organized by the International Centre for Theoretical Sciences. Learn about the intersection of pure mathematics and data-driven approaches in handling large-scale, noisy datasets. Gain insights into the analytic and algorithmic aspects of data science, focusing on probabilistic and optimization techniques. Understand how this field is revolutionizing traditional sciences and engineering, drawing parallels to the industrial revolution in its impact on data generation, storage, and processing.

Fitting Manifolds to Data with Large Noise by Hari Narayanan