Difference between revisions of "10-601 Perceptrons and Voted Perceptrons"
From Cohen Courses
Jump to navigationJump to search| Line 10: | Line 10: | ||
* Optional reading: Freund, Yoav, and Robert E. Schapire. "Large margin classification using the perceptron algorithm." Machine learning 37.3 (1999): 277-296. | * Optional reading: Freund, Yoav, and Robert E. Schapire. "Large margin classification using the perceptron algorithm." Machine learning 37.3 (1999): 277-296. | ||
* Optional background on linear algebra: [http://www.cs.cmu.edu/~zkolter/course/linalg/ Zico Kolter's linear algebra review lectures] | * Optional background on linear algebra: [http://www.cs.cmu.edu/~zkolter/course/linalg/ Zico Kolter's linear algebra review lectures] | ||
| − | |||
| − | |||
| − | |||
| − | |||
=== What You Should Know Afterward === | === What You Should Know Afterward === | ||
Revision as of 12:47, 24 September 2013
This a lecture used in the Syllabus for Machine Learning 10-601
Slides
Readings
- My notes on the voted perceptron. (You can skip sections 3-4 on ranking and the structured perceptron).
- Optional reading: Freund, Yoav, and Robert E. Schapire. "Large margin classification using the perceptron algorithm." Machine learning 37.3 (1999): 277-296.
- Optional background on linear algebra: Zico Kolter's linear algebra review lectures
What You Should Know Afterward
- The difference between an on-line and batch algorithm.
- How to implement the voted perceptron.
- The definition of a mistake bound, and a margin.
