Difference between revisions of "Class meeting for 10-605 Graph Architectures for ML"

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* TBD
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* Slides [http://www.cs.cmu.edu/~wcohen/10-605/graph-arch.pptx in powerpoint], [http://www.cs.cmu.edu/~wcohen/10-605/graph-arch.pdf in pdf]
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=== Quiz ===
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* [https://qna.cs.cmu.edu/#/pages/view/89 Today's Quiz].
  
 
=== 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].
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* Philip Stutz, Abraham Bernstein and William W. Cohen (2010): [http://www.cs.cmu.edu/~wcohen/10-605/swj566.pdf Signal/Collect: Graph Processing Large Graphs In Seconds] in ISWC-2010.
  
 
=== Things to Remember and/or Think About ===
 
=== Things to Remember and/or Think About ===
  
 
* Differences and commonalities between the graph-processing methods discussed: Pregel, Signal-Collect, GraphX, and GraphChi.
 
* 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.
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* How graph-processing approaches could be used for ML problems that will be studied in class, like SSL, PIC, and LDA.
 
* How operations on graphs can be implemented in dataflow languages.
 
* How operations on graphs can be implemented in dataflow languages.

Latest revision as of 13:57, 9 November 2017

This is one of the class meetings on the schedule for the course Machine Learning with Large Datasets 10-605 in Fall 2016.

Slides

Quiz

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 that will be studied in class, like SSL, PIC, and LDA.
  • How operations on graphs can be implemented in dataflow languages.