# Class meeting for 10-605 SGD for MF

From Cohen Courses

This is one of the class meetings on the schedule for the course Machine Learning with Large Datasets 10-605 in Fall_2017.

## Contents |

### Slides

### Quiz

### Papers Discussed

- Large-Scale Matrix Factorization with Distributed Stochastic Gradient Descent, Gemulla et al, KDD 2011.

### Things to Remember

- Definition of matrix factorization
- Common applications of matrix factorization, and how they map into the MF problem
- Loss functions for matrix factorization that are appropriate for collaborative filtering
- Algorithm and updates for SGD implementation of matrix factorization
- dSGD algorithm - what is done in parallel and what is done sequentially
- Definitions: stratum, interchangable steps, diagonal