Difference between revisions of "Class meeting for 10-605 Graph Architectures for ML"
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* 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. | + | * 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. | ||
Revision as of 14:00, 9 November 2016
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
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.
