Difference between revisions of "Class meeting for 10-405 SGD for MF"
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| − | This is one of the class meetings on the [[Syllabus for Machine Learning with Large Datasets 10- | + | This is one of the class meetings on the [[Syllabus for Machine Learning with Large Datasets 10-405 in Spring 2018|schedule]] for the course [[Machine Learning with Large Datasets 10-405 in Spring 2018|Machine Learning with Large Datasets 10-405 in Spring 2018]]. |
=== Slides === | === Slides === | ||
| − | * [http://www.cs.cmu.edu/~wcohen/10- | + | * [http://www.cs.cmu.edu/~wcohen/10-405/sgd-for-mf.pptx Matrix Factorization via SGD- Powerpoint] |
| − | * [http://www.cs.cmu.edu/~wcohen/10- | + | * [http://www.cs.cmu.edu/~wcohen/10-405/sgd-for-mf.pdf Matrix Factorization via SGD - PDF] |
=== Quiz === | === Quiz === | ||
Revision as of 18:12, 12 January 2018
This is one of the class meetings on the schedule for the course Machine Learning with Large Datasets 10-405 in Spring 2018.
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
