Back to Videos
This is a video about Boosting and Low-rank

Boosting and Low-rank

June 24, 2013
IMA
Presenters: Bin Yu

Watch Video 

Abstract

Boosting is one of the two most successful machine learning methods
with SVM. It uses gradient descent to an empirical loss function.
When the step sizes are small, it is computationally efficient way
to approximate Lasso. When a nuclear norm penalization is applied to L2
loss,
we have the low-rank regularization arising from the Netflix competition.
A subset of the netflix data will be investigated.