YoVDO

Graphs of Random Matrices in Deep Learning

Offered By: Fields Institute via YouTube

Tags

Random Matrix Theory Courses Machine Learning Courses Deep Learning Courses Neural Networks Courses Graph Theory Courses Mathematical Modeling Courses Dynamical Systems Courses

Course Description

Overview

Save Big on Coursera Plus. 7,000+ courses at $160 off. Limited Time Only!
Explore the intersection of random matrix theory and deep learning in this 25-minute lecture by Cristopher Salvi from Imperial College London. Delve into the fascinating world of graphs of random matrices and their applications in neural networks, gaining insights into how these mathematical structures influence the behavior and performance of deep learning models. Presented as part of the Fourth Symposium on Machine Learning and Dynamical Systems at the Fields Institute, this talk offers a unique perspective on the theoretical foundations underpinning modern machine learning algorithms.

Syllabus

Graphs of Random Matrices in Deep Learning


Taught by

Fields Institute

Related Courses

Neural Networks for Machine Learning
University of Toronto via Coursera Good Brain, Bad Brain: Basics
University of Birmingham via FutureLearn Statistical Learning with R
Stanford University via edX Machine Learning 1—Supervised Learning
Brown University via Udacity Fundamentals of Neuroscience, Part 2: Neurons and Networks
Harvard University via edX