Class meeting for 10-405 SGD for MF
From Cohen Courses
Revision as of 11:39, 5 March 2018 by Wcohen
This is one of the class meetings on the schedule for the course Machine Learning with Large Datasets 10-405 in Spring 2018.
- 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 (aka "diagonal"), interchangable steps