Difference between revisions of "Class meeting for 10-605 GraphLab"

From Cohen Courses
Jump to navigationJump to search
 
(6 intermediate revisions by the same user not shown)
Line 1: Line 1:
This is one of the class meetings on the [[Syllabus for Machine Learning with Large Datasets 10-605 in Spring 2015|schedule]] for the course [[Machine Learning with Large Datasets 10-605 in Spring_2015]].
+
This is one of the class meetings on the [[Syllabus for Machine Learning with Large Datasets 10-605 in Fall 2015|schedule]] for the course [[Machine Learning with Large Datasets 10-605 in Fall 2015]].
  
 
=== Slides ===
 
=== Slides ===
  
  
* [http://www.cs.cmu.edu/~wcohen/10-605/pregel-etc.pptx Pregel and other models]
+
* [http://www.cs.cmu.edu/~wcohen/10-605/pregel-etc.pptx Pregel and other models - part 1], [http://www.cs.cmu.edu/~wcohen/10-605/pregel-etc.pdf PDF version]
 +
* [http://www.cs.cmu.edu/~wcohen/10-605/pregel-etc-2.pptx Pregel and other models - part 2], [http://www.cs.cmu.edu/~wcohen/10-605/pregel-etc-2.pdf PDF version]
  
 
=== Readings ===
 
=== Readings ===
  
* None required.  Optional: Philip Stutz, Abraham Bernstein and William W. Cohen (2010): [http://www.cs.cmu.edu/~wcohen/postscript/iswc-2010.pdf Signal/Collect: Graph Algorithms for the (Semantic) Web] in ISWC-2010.  [http://www.cs.cmu.edu/~wcohen/10-605/swj566.pdf Longer version is also available] (under review).
+
* None required.  Optional: Philip Stutz, Abraham Bernstein and William W. Cohen (2010): [http://www.cs.cmu.edu/~wcohen/postscript/iswc-2010.pdf Signal/Collect: Graph Algorithms for the (Semantic) Web] in ISWC-2010.  [http://www.cs.cmu.edu/~wcohen/10-605/swj566.pdf Longer version is also available].
 +
 
 +
=== Things to Remember and/or Think About ===
 +
 
 +
* Differences and commonalities between the graph-processing methods discussed: Pregel, Signal-Collect, GraphX, and GraphChi.
 +
* How graph-processing approaches could be used for ML problems studied in class, like SSL, PIC, and LDA.
 +
* How operations on graphs can be implemented in dataflow languages.

Latest revision as of 17:33, 6 December 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

Readings

Things to Remember and/or Think About

  • Differences and commonalities between the graph-processing methods discussed: Pregel, Signal-Collect, GraphX, and GraphChi.
  • How graph-processing approaches could be used for ML problems studied in class, like SSL, PIC, and LDA.
  • How operations on graphs can be implemented in dataflow languages.