Randomized Least Squares Optimization and its Incredible Utility for Large-Scale Tensor Decomposition
Offered By: Simons Institute via YouTube
Course Description
Overview
Explore randomized least squares optimization and its powerful applications in large-scale tensor decomposition in this 33-minute talk by Tamara Kolda from MathSci.ai. Delivered as part of the Extroverted Sublinear Algorithms series at the Simons Institute, delve into the innovative techniques and methodologies that are revolutionizing the field of tensor decomposition. Gain insights into how these advanced optimization methods can be leveraged to tackle complex computational challenges in data analysis and machine learning.
Syllabus
Randomized Least Squares Optimization and its Incredible Utility for Large-Scale Tensor Decomp...
Taught by
Simons Institute
Related Courses
Big Data Analytics in HealthcareGeorgia Institute of Technology via Udacity Introduction to Recommender Systems
University of Minnesota via Coursera Поиск структуры в данных
Moscow Institute of Physics and Technology via Coursera Materials Data Sciences and Informatics
Georgia Institute of Technology via Coursera Matrix Factorization and Advanced Techniques
University of Minnesota via Coursera