Difference between revisions of "Class meeting for 10-405 SGD for MF"

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* 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
* dSGD algorithm - what is done in parallel and what is done sequentially
+
* DSGD algorithm - what is done in parallel and what is done sequentially
* Definitions: stratum, interchangable steps, diagonal
+
* Definitions: stratum (aka "diagonal"), interchangable steps

Latest revision as of 12:39, 5 March 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

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