Difference between revisions of "Class meeting for 10-605 Parallel Perceptrons 1"
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− | This is one of the class meetings on the [[Syllabus for Machine Learning with Large Datasets 10-605 in | + | This is one of the class meetings on the [[Syllabus for Machine Learning with Large Datasets 10-605 in Fall 2015|schedule]] for the course [[Machine Learning with Large Datasets 10-605 in Spring_2015]]. |
=== Slides === | === Slides === | ||
− | * [http://www.cs.cmu.edu/~wcohen/10-605/mistake-bounds+struct-vp.pptx Slides in Powerpoint] | + | Catchup from Tuesday: |
+ | |||
+ | * [http://www.cs.cmu.edu/~wcohen/10-605/2016/sgd-part2.pptx Slides in Powerpoint] | ||
+ | * [http://www.cs.cmu.edu/~wcohen/10-605/2016/sgd-part2.pdf Slides in PDF] | ||
+ | |||
+ | Perceptrons: | ||
+ | |||
+ | * [http://www.cs.cmu.edu/~wcohen/10-605/2016/mistake-bounds+struct-vp-1.pptx Slides in Powerpoint] | ||
+ | * [http://www.cs.cmu.edu/~wcohen/10-605/2016/mistake-bounds+struct-vp-1.pdf Slides in PDF] | ||
=== Preparation for the Class === | === Preparation for the Class === | ||
− | * [http://www.cs.cmu.edu/~wcohen/10-601/vp-notes/vp.pdf | + | * Read [http://www.cs.cmu.edu/~wcohen/10-601/vp-notes/vp.pdf my notes on the voted perceptron]. Alternatively, or in addition, you can '''view the lecture''' for 10-601 from 9/22/14 or 9/23/14, which can be accessed [https://mediatech-stream.andrew.cmu.edu/Mediasite/Catalog/Full/4e86c44694a14b9fbe1ea7653f553ac621 via MediaTech]. |
+ | |||
* 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, if you need it: [http://www.cs.cmu.edu/~zkolter/course/linalg/ Zico Kolter's linear algebra review lectures] | ||
+ | |||
+ | === What You Should Remember === | ||
+ | |||
+ | * The perceptron algorithm, and its complexity | ||
+ | * Definitions: mistake, mistake bound, margin |
Latest revision as of 16:40, 1 August 2017
This is one of the class meetings on the schedule for the course Machine Learning with Large Datasets 10-605 in Spring_2015.
Slides
Catchup from Tuesday:
Perceptrons:
Preparation for the Class
- Read my notes on the voted perceptron. Alternatively, or in addition, you can view the lecture for 10-601 from 9/22/14 or 9/23/14, which can be accessed via MediaTech.
- 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, if you need it: Zico Kolter's linear algebra review lectures
What You Should Remember
- The perceptron algorithm, and its complexity
- Definitions: mistake, mistake bound, margin