Difference between revisions of "Class meeting for 10-605 Unsupervised Learning On Graphs"
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=== Optional Readings === | === Optional Readings === | ||
| + | * Von Luxburg, Ulrike. "A tutorial on spectral clustering." Statistics and computing 17.4 (2007): 395-416. | ||
* Frank Lin and William W. Cohen (2010): Power Iteration Clustering in ICML-2010. | * Frank Lin and William W. Cohen (2010): Power Iteration Clustering in ICML-2010. | ||
* Frank Lin and William W. Cohen (2010): A Very Fast Method for Clustering Big Text Datasets in ECAI-2010. | * Frank Lin and William W. Cohen (2010): A Very Fast Method for Clustering Big Text Datasets in ECAI-2010. | ||
* Frank Lin and William W. Cohen (2011): Adaptation of Graph-Based Semi-Supervised Methods to Large-Scale Text Data in MLG-2011. | * Frank Lin and William W. Cohen (2011): Adaptation of Graph-Based Semi-Supervised Methods to Large-Scale Text Data in MLG-2011. | ||
* Ramnath Balasubramanyan, Frank Lin, and William W. Cohen (2010): Node Clustering in Graphs: An Empirical Study in NIPS-2010 Workshop on Networks Across Disciplines. | * Ramnath Balasubramanyan, Frank Lin, and William W. Cohen (2010): Node Clustering in Graphs: An Empirical Study in NIPS-2010 Workshop on Networks Across Disciplines. | ||
Revision as of 12:43, 17 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
Quiz
- There's no quiz today.
Optional Readings
- Von Luxburg, Ulrike. "A tutorial on spectral clustering." Statistics and computing 17.4 (2007): 395-416.
- Frank Lin and William W. Cohen (2010): Power Iteration Clustering in ICML-2010.
- Frank Lin and William W. Cohen (2010): A Very Fast Method for Clustering Big Text Datasets in ECAI-2010.
- Frank Lin and William W. Cohen (2011): Adaptation of Graph-Based Semi-Supervised Methods to Large-Scale Text Data in MLG-2011.
- Ramnath Balasubramanyan, Frank Lin, and William W. Cohen (2010): Node Clustering in Graphs: An Empirical Study in NIPS-2010 Workshop on Networks Across Disciplines.
