Difference between revisions of "Class meeting for 10-605 SGD for MF"
From Cohen Courses
Jump to navigationJump to searchLine 17: | Line 17: | ||
* Definition of matrix factorization | * Definition of matrix factorization | ||
− | * Common applications 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 | * Loss functions for matrix factorization that are appropriate for collaborative filtering | ||
* Algorithm and updates for SGD implementation of matrix factorization | * Algorithm and updates for SGD implementation of matrix factorization | ||
− | * Definitions: stratum, | + | * dSGD algorithm - what is done in parallel and what is done sequentially |
+ | * Definitions: stratum, interchangable steps, diagonal |
Revision as of 16:05, 16 October 2015
This is one of the class meetings on the schedule for the course Machine Learning with Large Datasets 10-605 in Fall_2015.
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