Difference between revisions of "Class meeting for 10-605 SGD and Hash Kernels"
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* [http://www.cs.cmu.edu/~wcohen/10-605/sgd.pptx Slides in Powerpoint] | * [http://www.cs.cmu.edu/~wcohen/10-605/sgd.pptx Slides in Powerpoint] | ||
* [http://www.cs.cmu.edu/~wcohen/10-605/sgd.pdf Slides in PDF] | * [http://www.cs.cmu.edu/~wcohen/10-605/sgd.pdf Slides in PDF] | ||
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| + | Addendum, covered in Thursday's class: | ||
| + | * [http://www.cs.cmu.edu/~wcohen/10-605/sgd-addendum.pptx Slides in Powerpoint] | ||
| + | * [http://www.cs.cmu.edu/~wcohen/10-605/sgd-addendum.pdf Slides in Powerpoint] | ||
=== Readings for the Class === | === Readings for the Class === | ||
Revision as of 18:49, 18 February 2015
This is one of the class meetings on the schedule for the course Machine Learning with Large Datasets 10-605 in Spring_2015.
Slides
Stochastic gradient descent:
Addendum, covered in Thursday's class:
Readings for the Class
Optional readings
- For logistic regression, and the sparse updates for it: Lazy Sparse Stochastic Gradient Descent for Regularized Multinomial Logistic Regression, Carpenter, Bob. 2008. See also his blog post on logistic regression. I also recommend Charles Elkan's notes on logistic regression (local saved copy).
- For hash kernels: Feature Hashing for Large Scale Multitask Learning, Weinberger et al, ICML 2009.
