Difference between revisions of "Class meeting for 10-605 Graph Architectures for ML"
From Cohen Courses
Jump to navigationJump to search (→Slides) |
(→Slides) |
||
| Line 4: | Line 4: | ||
| − | * Slides [http://www.cs.cmu.edu/~wcohen/10-605 | + | * 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] |
=== Quiz === | === Quiz === | ||
Revision as of 13:56, 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
- Slides in powerpoint, in pdf
Quiz
Readings
- Philip Stutz, Abraham Bernstein and William W. Cohen (2010): Signal/Collect: Graph Algorithms for the (Semantic) Web in ISWC-2010. 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 that will be studied in class, like SSL, PIC, and LDA.
- How operations on graphs can be implemented in dataflow languages.
